An Industrial West? A Mixed-Methods Analysis of Newspapers Discourses about Technology over One Hundred and Ten Years (1830-1940)

Abstract

Recent work analyzing the social impact of technology in processes of globalization signals a shared Western voice in sustainability related discourses dating back twenty years (Fernández Fernández and Savcisens [1]). However, many scholars propose the idea that, as a direct consequence of the Second Industrial Revolution, globalization processes can be traced back at least to the second half of the nineteenth century. Only a few decades later, nevertheless, two of the most divisive historic events ever in human history took place: the First and Second World Wars. In this article we seek to explore information behaviour during one hundred and ten years approximately (1830-1940), using multilingual historic newspapers as a proxy (Le Figaro, The New York Herald, El Imparcial, Neuer Hamburger Zeitung and La Stampa), to observe to what extent technology acted as a cohesive force across Western societies walking along these different historic happenings. Thus we filter our corpus with three key technological terms (telephone, gasoline, and iron) as an exploratory endeavour. Afterwards, we implement a mix-methods approach that combines quantitative and qualitative research methodologies. In our quantitative analysis, we use a five-step pipeline that includes Topic Modelling (Pachinko Allocation), translation of the topic words into English, Word Embeddings, Ward Hierarchical Clustering, and a directed graph. In our qualitative analysis, we firstly select randomly one newspaper per decade per outlet seeking to observe whether multilingual historical newspapers are comparable objects of analysis (i.e. is their format similar enough to implement meaningful discourse analysis?). Secondly, we also sample randomly a variety of articles containing our selected key terms in order to assess the social impact of technology using a close reading approach. Our quantitative data analysis reveals three main findings: firstly, we empirically detect a trend in information flattening coinciding with the peak of the Second Industrial Revolution (1890 and 1900), as well as a trend of information complexity during the following decades. Secondly, we observe more nuanced patterns of agreement during the Twentieth century, therefore showing how the social and political polarity during that time did not affect technological related discourses. Thirdly, we notice high rates of content similarity across our three selected key terms over our whole observational time, displaying almost identical wording. These findings resonate with our qualitative analysis, where we observe a certain degree of heterogeneity among both newspapers formatting and our selection of articles, yet very subtly. These outcomes make us speculate with the idea that it is possible to trace a shared Western voice in technological related discourses back to two hundred years ago, exposing the agency of technology as a trigger of cultural flattening in terms of information behaviour.

Full text

1
An Industrial West? A Mixed-Methods Analysis of
Newspapers Discourses about Technology over One
Hundred and Ten Years (1830-1940)
Emmanuelle Denove1, Elisa Michelet2, Germans Savcisens3, Elena Fern´
andez Fern´
andez4.
1 2 Department of Computer Science, EPFL, Rte Cantonale, 1015 Lausanne, Switzerland
3Section for Cognitive Systems, Technical University of Denmark, Building 324, Kongens Lyngby 2800, Denmark
4Institute of Computational Linguistics, University of Zurich, University of Zurich, Andreas Strasse 15, Zurich,
8050, Switzerland.
{emmanuelle.denove, elisa.michelet}@epfl.ch, gersa@dtu.dk, elena.fernandezfernandez@uzh.ch
Abstract—Recent work analyzing the social impact of tech-
nology in processes of globalization signals a shared Western
voice in sustainability related discourses dating back twenty
years (Fern´
andez Fern´
andez and Savcisens [1]). However, many
scholars propose the idea that, as a direct consequence of the
Second Industrial Revolution, globalization processes can be
traced back at least to the second half of the nineteenth century.
Only a few decades later, nevertheless, two of the most divisive
historic events ever in human history took place: the First and
Second World Wars. In this article we seek to explore information
behaviour during one hundred and ten years approximately
(1830-1940), using multilingual historic newspapers as a proxy
(Le Figaro, The New York Herald, El Imparcial, Neuer Hamburger
Zeitung and La Stampa), to observe to what extent technology
acted as a cohesive force across Western societies walking along
these different historic happenings. Thus we filter our corpus with
three key technological terms (telephone, gasoline, and iron) as an
exploratory endeavour. Afterwards, we implement a mix-methods
approach that combines quantitative and qualitative research
methodologies. In our quantitative analysis, we use a five-step
pipeline that includes Topic Modelling (Pachinko Allocation),
translation of the topic words into English, Word Embeddings,
Ward Hierarchical Clustering, and a directed graph. In our
qualitative analysis, we firstly select randomly one newspaper
per decade per outlet seeking to observe whether multilingual
historical newspapers are comparable objects of analysis (i.e. is
their format similar enough to implement meaningful discourse
analysis?). Secondly, we also sample randomly a variety of
articles containing our selected key terms in order to assess the
social impact of technology using a close reading approach. Our
quantitative data analysis reveals three main findings: firstly, we
empirically detect a trend in information flattening coinciding
with the peak of the Second Industrial Revolution (1890 and
1900), as well as a trend of information complexity during the
following decades. Secondly, we observe more nuanced patterns
of agreement during the Twentieth century, therefore showing
how the social and political polarity during that time did not
affect technological related discourses. Thirdly, we notice high
rates of content similarity across our three selected key terms
over our whole observational time, displaying almost identical
wording. These findings resonate with our qualitative analysis,
where we observe a certain degree of heterogeneity among both
newspapers formatting and our selection of articles, yet very
subtly. These outcomes make us speculate with the idea that
it is possible to trace a shared Western voice in technological
related discourses back to two hundred years ago, exposing the
agency of technology as a trigger of cultural flattening in terms
of information behaviour.
I. INTRODUCTION
Contemporary perceptions about technology tend to frame
the latest digital revolution as responsible for triggering an
unprecedented wave of social changes in Eurocentric, industri-
alized societies (Smil [2]). Placed by some authors during the
last decades of the twentieth century (Castells [3], Wajcman
[4]) under the label of post-industrialism, it has been empiri-
cally proven that the number of technical innovations arriving
to society during the last thirty years is indeed dramatically
higher than at any other period of recorded history (Kelly
et al. [5]). Yet some authors signal the latest decades of
the nineteenth century as a moment when a rapid influx of
technological inventions not only profoundly changed social
life across the Western world at a coetaneous level but had the
capacity of imprinting long-lasting historical and social effects
that can be traced up to our present-day times (Smil [2]):
That period ranks as history’s most remarkable dis-
continuity not only because of the extensive sweep
of its innovations but also because of the rapidity
of fundamental advances that were achieved during
that time. (6)
The Second Industrial Revolution has been extensively
analyzed across countries from historic (Stearns [6]), economic
(Cipolla [7]), and geographic perspectives (King and Timmis
[8]). Coetaneous views expressed by nineteenth century citi-
zens regarding the profound social and historic changes that
the Industrial Revolution was imprinting in society have as
well received some critical attention, mostly in the field of
Social History (King and Timmis [8]): “We suggest that there
was a widely view amongst contemporaries that, irrespective
of whether or not they approved, theirs was a society un-
dergoing substantial change. They felt that ’something was
happening’ much as the Internet gives modern society a feeling
of cumulative and fundamental change”. (6)
This paper seeks to engage with these academic conversa-
tions by contributing with the analysis of a yet unexplored
aspect: we aim to observe the social impact of technology by
inspecting its agency as a trigger of information homogeniza-
tion and cultural flattening across time (one hundred and ten
years) and space (five different countries: Spain, France, Italy,

2
Germany, and The United States) using multilingual historical
newspapers as a proxy. We define information homogenization
as a lack of semantic diversity in our data processing, outputted
by a five step pipeline (that we borrow from Fern´
andez
Fern´
andez and Savcisens [1]) consisting of firstly using topic
modelling on a key-term (telephone, gasoline, and iron) filtered
sample of our multilingual newspaper corpus, followed by
an English translation of the Topic Modelling multilingual
words. Afterwards we use word embeddings to detect semantic
proximity across those words, and then we implement Ward
Hierarchical Clustering and a directed graph to accomplish
yet another round of semantic affinity filtering and only
select topics that are very similar across newspapers. High
rates of semantic similarity in our data analysis could be
understood as a proxy of technologically related information
being reported similarly across our observational countries. We
define cultural flattening as a process of social standardization
as a consequence of a similar assimilation of our selected
technological-related terms in our different objects of study
(multilingual historical newspapers).
Recent work by Fern´
andez Fern´
andez and Savcisens [1])
claims the existence of growing patterns of information agree-
ment in contemporary press discourses about sustainability
(1999-2018), as well as the existence of a clearly streamed
Western voice that can be traced back up to twenty years ago,
yet becoming more pronounced as we approach contemporary
times. The authors argue that contemporary newspapers of
record across Western countries (The Times, El Pa´
ıs, Le
Figaro, The New York Times International, NZZ, La Stampa)
encode very similarly sustainability related discourses, provid-
ing highly homogeneous information to multilingual readers
of their respective countries. These findings resonate with the
ideas presented by other authors such as Herman and Chomsky
( [9]), who also note qualitatively the homogeneity of Western
media. However, unlike Fern´
andez Fern´
andez and Savcisens
( [1]), Hermans and Chomsky ( [9]) argue that Western mass
media is controlled by private corporations and Governments
seeking to influence public opinion worldwide (the propaganda
model, so to speak).
In this paper we seek to engage with these academic
conversations, and specifically with the ideas presented by
Fern´
andez Fern´
andez and Savcisnes [1], as we are intrigued to
explore a) whether their findings are exclusive to sustainability
related discourses or if similar trends in information behaviour
could be detected in technologically related ones broadly
speaking, and b) if it is possible to note trends of information
homogenization as early as the mid-nineteenth century or
if it is an exclusive twentieth-first century phenomenon. In
order to do so, we quantitatively analyze Western public
discourses as recorded by historic multilingual newspapers
about technological innovations either arriving to society dur-
ing the nineteenth century (such as the telephone) or being
widely used during this historical time (such as gasoline
and iron), in order to observe to what extend their press
coverage was similar or different across time and space during
a time-spam of one hundred and ten years (1830-1940). Our
observational time coincides with profound social changes that
hastened processes of cultural flattening (such as a first peak of
globalization during the last decades of the nineteenth century)
as well as intense social and political division (the First and
Second World Wars, and the interwar period).
We follow the definition of globalization proposed by
Stearns [6]: “Globalization is simply the intensification of
contacts among different parts of the world and the creation of
networks that, combined with more local factors, increasingly
shape human life” (2). We also agree with both Stearns [6]
and Robertson [10] proposal that understands globalization as
a gradual historic process with roots that can be traced back to
1000 CE, rushed by specific historic moments. And, again in
agreement with both of them, we also consider the second half
of the nineteenth century one of the most crucial moments in
recent human history, coinciding with the climax of the Second
Industrial Revolution (Stearns [6]):
The industrial revolution effectively caused the mod-
ern version of globalization. In turn, globalization,
particularly since the mid-nineteenth century, has
reshaped the industrial experience in many ways.
The connection first became clear in the late nine-
teenth century, when international trade grew at
unprecedented rate. (225)
The nineteenth century witnessed as well the rise of the
modern nation around the second half of the nineteenth
century following the collective wave of revolutions of 1848
(Hobsbawm ( [11]). The role of the press as a force of national
cohesion and identity building has been discussed by authors
like Anderson ( [12]), who proposes how during the second
half of the nineteenth century, Western citizens would engage
in a daily newspaper reading ritual across their respective
countries. This collective action of simultaneously reading
a same commodified object (newspapers of record) would
create a shared feeling of community contributing to foster
the creation of a common national identity at a foundational
moment of history. In this paper we seek to make a different
argument though. While we do not disagree with Anderson, we
are mostly interested in observing how discourses about tech-
nological innovations were encoded similarly or differently in
the press as we consider historic multilingual newspapers an
ideal medium where to analyze the social impact of technology
as a trigger of cultural flattening.
Thus we use as a proxy a dataset of multilingual his-
toric newspapers (Spanish: El Imparcial, French: Le Figaro,
English: The New York Herald, German: Neuer Hamburger
Zeitung, and Italian: La Stampa). We select three technological
related terms: gasoline, iron, and telephone, and filter our
corpus with them, as a first exploratory approach in the
analysis of public discourses about technology. Our selection
of these terms is motivated by Smil’s ideas ( [2]), who
signals these technologies as important elements within the
categories of combustion engines, new materials and new
synthesis, or communication and information, that he uses
to segment the Second Industrial Revolution into different
thematic sections. In dialogue with Smil (Smil), we believe
that those were mainstream technologies that were widely
used across our countries of choice during our observational
time, and consequently, should be considered as relevant study

3
cases for a first approximation to the analysis of the agency
of technology as a actor of cultural flattening.
Afterwards, and as mentioned, we follow the five-step
pipeline proposed by Fern´
andez Fern´
andez and Savcisens (
[1]), seeking to track rates of homogeneity versus heterogene-
ity of information across countries as well as their temporal
evolution. This pipeline is written as independently as possible
of language and archival type, and can easily be adapted
to support more languages and parse other newspapers. We
interpret less diversity of topics as a signal of information
homogeneity, and speculate with the idea that this uniformity
in press discourses could be considered as a shared Western
voice that may signal the existence of a common technolog-
ically related shared press identity. By extension, we argue
that technology could be considered as an element of cultural
cohesion across Western societies that can be observed as early
as the second half of the nineteenth century and that co-exists
and over-performs both global processes of globalization and
episodes of social polarization such as the First and Second
World Wars.
Additionally, we implement a qualitative research method-
ology seeking to complement our quantitative data analysis.
In order to assess whether multilingual historical newspapers
are comparable objects of discourse analysis from a formatting
perspective (i.e. newspaper’s sections, article length, font size,
or advertising), we select randomly one newspaper per decade
per publication (a total of forty one newspapers). We also
inspect a randomized sample of articles containing our three
key terms selected from all our publications. We seek to
assess qualitatively how discourses reflect the social impact
of technology in order to have a better understanding of our
dataset, and by extension, implement a better interpretation of
our data analysis outcomes.
II. STATE OF THE ART
The Industrial Revolution and its impact in society has
received a considerable amount of attention across disciplines.
Existing state of the art qualitatively has focused its attention
on topics such as world history (Stearns [6]), geography (King
and Timmis [8]), or economic history (Cipolla [7]). Further-
more, the historic specificities of different countries during
this period of time have been as well extensively analyzed
by scholarly critique (Vilar [13], Veblen [14], Gomellini and
Toniolo [15]; just to mention a few).
In recent years, the field of Digital Humanities has con-
tributed with new and highly innovative perspectives to ex-
isting qualitative analysis about the Industrial Revolution by
using computational methods in the analysis of the past. Yet
existing work has been accomplished using predominantly
English sources. Under the umbrella of the research project
Living with Machines (based at the Alan Turing Institute in
London), a variety of new tools, research articles, datasets, and
methodologies have been developed to deepen the analysis
of the Industrial Revolution in the United Kingdom using
Victorian British newspapers as an object of study. Coll
Ardanuy et al. [16] use historic newspapers in English to
create a knowledge base in which toponyms appearing in the
press are linked to real-life geographic locations. Beleen et
al. [17] challenge the utility of digitized historical newspapers
as historical objects of analysis of their contemporary time
of publication by questioning the fragments of society and
reality that they capture and therefore calling into question
the readings of the past that they facilitate. Similarly, Beleen
et al. [18], question the bias of the British Newspapers
Archive in terms of range (historical coverage), demographic
representation, and OCR quality.
In this paper, we seek to dialogue with existing scholarly
work, qualitatively and quantitatively, and across fields, in their
analysis of the Second Industrial Revolution. Our major contri-
bution lies in the investigation of the agency of technology in
shaping information behaviour during the nineteenth and early-
twentieth centuries, and specifically, as a trigger of cultural
flattening and information homogenization.
Furthermore, and as mentioned, we predominantly dialogue
with Fern´
andez Fern´
andez and Savicens [1]. The authors use a
dataset of multilingual newspapers (English, French, German,
Italian, and Spanish), over a time-span of twenty years (1999-
2018), using the same pipeline that we implement in this paper
yet targeting sustainability related discourses. Their findings
show increasing trends of information homogeneity as we
approach contemporary times, relating processes of global-
ization and information homogenization. Moreover, they also
note high rates of information uniformity overall, showcasing
a clear Western common voice that can be traced back to the
last twenty years. We seek to expand their analysis, and by
using one hundred and ten extra years of data (1830-1940 to
complement their 1999-2018 observational time) we cover in
total almost two hundred years of Western history, therefore
contributing to deepening our understanding about the historic
role of technology in processes of Western identity formation.
III. CORPUS
Our dataset is composed of a variety of historical multilin-
gual newspapers in English (The New York Herald), French
Le Figaro, German (Neue Hamburger Zeitung), Spanish (El
Imparcial), and Italian (La Stampa). Our observational time
covers one hundred and ten years (1830-1940). During that
time some newspapers experienced different ownership phases,
and by extension, also changing ideological management.
Le Figaro is known for its historic conservative centered-
right political orientation (Kuhn [19]), while The New York
Herald was a slightly sensationalized outlet, yet the most suc-
cessful and widely circulated newspaper in the second half of
the nineteenth century in the United States (Crouthamel [20])).
El Imparcial held progressive (liberal) views (Bahamonde
Magro and Otero Carvajal ( [21]). La Stampa showed a similar
political orientation than Le Figaro: slightly conservative,
leaning towards the social and political views of industrial-
capitalist readership. Moreover, during our observational time,
it was a somewhat regional newspaper mostly focusing on the
Turin area, only becoming one of Italy’s newspaper of record
during the second half of the twentieth century (Saitta [22]).
Neue Hamburger Zeitung, very similarly to La Stampa, tar-
geted an educated and intellectually active readership (Tornier

4
( [23])). So, in spite of being a relatively regional newspaper,
it included extensive coverage of international and national
affairs. Consequently, although our corpus presents some de-
gree of heterogeneity in terms of scope and readership, we
believe that our selected newspapers are similar enough to
perform a meaningful cross-cultural comparison to inspect the
social impact of technology in Western countries across our
observational time.
Our motivation for choosing these newspapers is fundamen-
tally related to availability. The authors of this article are fluent
in English, Spanish, French, and German, and their domain
knowledge expertise focuses on Western nations where those
languages are spoken. Moreover, we are interested in selecting
newspapers with a tendency towards politically-centered views
across countries with large historical availability covering our
observational time (1830-1940) accessible in a data-mining
friendly format. We are particularly interested in building a
corpus of relatively similar textual objects across countries
approximately targeting similar scope and readership and
therefore facilitating a relevant multi-cultural analysis when it
comes to identify the agency of technology as a cross-border
trigger of information flattening.
While our corpus is not complete (there are some decades
missing) this is a common-place scenario in open source
historical newspapers datasets, and a challenge that Digital
Humanists frequently encounter. Although we are aware of
the limitations that our corpus presents when it comes to the
articulation of our main thesis (the agency of technology as
a trigger of information homogenization and by extension of
cultural flattening), we still believe that it provides a relevant
medium of analysis where to observe the social impact of
technology in Western public discourses.
Each newspaper has been retrieved from different sources
and presents different historical ranges and accessibility. Table
1 describes each newspaper’s range of available dates as well
as retrieving source, and figure 1 provides a cross-newspaper
comparison of newspaper availability.
IV. COR PU S QUALITY
The raw data for these newspapers was gathered by digi-
tising the original issues using Optical Character Recognition
(OCR). Since this method is not reliable and regularly results
in errors, determining the corpus quality is necessary. To
achieve this, Thomas Benchetrit’s OCR-qualification pipeline
[24] was used. It represents text quality as the proportion of
words in a document that were correctly digitised, which is
determined by checking whether they exist in the respective
language’s dictionary. Assuming that words are either digitised
correctly or not (i.e. no word is digitised as a different valid
word), this metric gives us a percentage of overall text cor-
rectness. The dictionaries used here are the ones provided by
the Enchant spellchecking library. The results are documented
in Figure 2.
V. ARTICLE SPLITTING
The data of each newspaper was provided in the form of
”documents” which gathered the newspaper text in different
ways, namely :
Fig. 1. Newspapers Data Availability
Fig. 2. OCR quality of newspapers
•Le Figaro : one ”document” is an entire newspaper for
a given day, with no clear delimitation between articles.
•El Imparcial : like for Le Figaro, one ”document” is an
entire newspaper for a given day. However, very often,
different articles are separated by a newline.
•Neue Hamburger Zeitung : there is one ”document” per
article.
•La Stampa : there is one ”document” per article.
•New York Herald : one ”document” represents one page
of a newspaper issue for a given day. Within these pages,
there is no clear delimitation between articles.
For topic modeling, this lack of delimitation between ar-

5
TABLE I
CORPUS AVAILABILITY AND SOURCES
Journal Time Period Source
Le Figaro 1860-1920 Gallica
The New York Herald 1840-1888, 1920 Library of Congress
El Imparcial 1860-1930 Biblioteca Nacional de Espa˜
na
La Stampa 1882, 1910-1930 La Stampa Archives (by Bas et al.)
Neuer Hamburger Zeitung 1888-1930 Staats- und Universitaetsbibliothek Hamburg Carl von Ossietzky.
ticles is problematic. Since entire newspaper issues, or even
a single page of one newspaper issue, often contain many
articles that tackle different topics, trying to perform topic
modeling on these unaltered documents would lead to very
confused and imprecise results. Therefore, a pipeline to split
these documents into individual articles is necessary. These
pipelines were determined empirically.
A. El Imparcial
Since most articles in the El Imparcial dataset are split by
a newline, we simply consider every line of each document
of length in characters l > 20 a distinct article. This method
was adopted from Elisa Michelet’s master project [25].
B. Le Figaro
The documents in this dataset contain many newlines that
don’t necessarily denote new articles. However, new articles
are preceded by a newline, and many of their titles are written
in uppercase. We therefore consider the beginning of a new
article any newline followed by a string of length lwhose
alphabetic characters are uppercase with a frequency larger
than k. Empirically, we determined for best results l= 30 and
k=2
3.
C. The New York Herald
This dataset provided the .xml documents from the OCR
as well as their textual interpretation. The XML files contain
information about the size in pixels of the detected words.
Since most titles of articles are written in a larger font than
the rest of the text, this allows us to split articles based on this
size information. More specifically, we consider the beginning
of a new article any part of the text such that there is a sudden
change in font size diffsize < f . Additionally, we require that
the first nwords of an article (i.e. the title) have uppercase
characters with a frequency larger than k. Empirically, we
determined f=−20,n= 2 and k=2
3.
VI. KE YW ORD DETECTION
To determine the conversations surrounding different tech-
nologies in the newspapers of our corpus, the articles were
filtered and only those that include the given keyword were
kept. The exact words used to filter the newspaper documents
are summarized in Table 2.
For simplicity, the words were filtered only in their basic
noun form. However, words that include the word root were
also included (e.g. “petroleum”, “telefonisch”). In the case
of gasoline, the synonym “petrol” was also considered, as
they are often used interchangeably. Since the keywords were
analyzed independently, no special consideration was given
to documents that contain multiple keywords. Specifically for
the keyword ”iron”, the filtering was done with a leading and
trailing whitespace, as shown in V-B. The word being so short,
filtering otherwise led to there being a very large number of
unrelated results due to the all words containing ”iron” as a
subpart.
We believe that our key terms (telephone, gasoline, iron)
belong to technologically specialized vocabulary, and there-
fore, aiming to avoid semantic ambiguity, we have decided to
not include any synonyms.
VII. MET HO DS
A. Topic Modeling
The goal of this article is to detect the nature and evolution
of discussions surrounding technology in different countries
over time. In order to determine how these subjects were
discussed in the newspapers in our corpus, we firstly use topic
modeling as a proxy to classify documents. Our goal is to a)
determine the degree of homogeneity vs heterogeneity in terms
of information encoding (i.e. our selected technical terms)
across our newspapers of choice, and b) perform a manual
reading to the multilingual words (translated into English)
outputted by our pipeline. Therefore, Topic Modelling is an
adequate method for our research needs.
1) Pachinko Allocation Model: The Pachinko Allocation
Model (PAM) [26] was used to detect topics in documents.
This model was chosen because it is able to capture correla-
tions between topics. It models the vocabulary as the leaves
of a Directed Acyclic Graph (DAG), and the topics as the
nodes. Correlations are then represented by the edges between
different nodes and leaves of the graph, which can be between
words or between topics, the latter resulting in a set of super-
topics.
Since PAM performs much better when the number of
super-topics and sub-topics is pre-defined [27], a grid search
is performed to obtain the optimal parameters. This process is
detailed below.
2) Best parameter calculation: To train a Pachinko model,
we require two arguments k1and k2denoting respectively
the number of super-topics and the number of sub-topics
in the corpus. Since we do not know these beforehand, we
create the model with all possible pairs of k1and k2with
k1∈[1,2] and k2∈[k1,14]. These values were chosen
empirically. To determine the best parameters, we compare
their coherence value, which is a metric that aims to quantify
the coherence and human interpretability of the top words per

6
TABLE II
KEY WOR DS US ED T O FILTE R ARTI CL ES
Gasoline Telephone Iron
French essence OR petrol telephone ” fer ”
Spanish gasolina OR petroleo telefono ” hierro ”
German benzin OR kraftstoff telefon OR telephon ” eisen ”
English gasoline OR petrol telephone ” iron ”
Italian benzina telefono ” fierro ”
topic returned by a topic model [28]. Specifically, the chosen
metric is cV-coherence because its results are the closest to
a human interpretation [25]. By default, the method used to
determine the best parameter is the one-standard-error rule,
which selects the model whose prediction error is at most one
standard error worse than that of the best model [29]. However,
this method is often quite ungenerous and only detects 1 or 2
subtopics. In those cases, we used the parameters of the best
model as determined by the grid search. Since the optimal
number of topics in a corpus changes based on the documents
used to train the model, this calculation was repeated for every
combination of keyword, newspaper and time-span.
B. Model training
Separate models were trained for every combination of
keyword, newspaper and time-span in order to track the
evolution of topics across time and newpapers. The pipeline
from pre-processed documents to trained model for a given
newspaper is:
•splitting the set of articles into time-spans of 10 years
•using Spacy [30] to retrieve the lemmas of words in the
articles, keeping only lemmas that are not stop words and
that are alphanumerical. Lemmas that have less than 4
characters were also discarded, since they often represent
noise from the OCR.
•determining the optimal number of super-topics and sub-
topics for the given model as described in section VII-A2
•using Tomotopy’s Pachinko Allocation training model
[31] to train the given model following the pipeline pro-
posed by [32] with the previously determined parameters
Finally, each given model was algorithmically described as
the set of its k= 15 most representative words as determined
by the topic modeling. From these keywords, an overarching
topic was manually assigned.
C. Topic Similarity
To cluster similar topics originating from different newspa-
pers, we calculate the similarity score between each pair of
topics. We do so separately per each time span, dialoguing
with Fern´
andez Fern´
andez and Savcisens ( [1]).
First, we start by estimating the similarity between inner
topics. To make the multilingual topic vectors γt, n, d com-
parable, we translate words associated with each topic vector
(from Italian, Spanish, German, and French) into English using
the Google Translate API. Since all translations were mapped
onto modern English, and the translation model is capable of
mapping “old” spellings to their modern counterparts, it is
reasonable to assume that the translations allow for linking
articles across time regardless of language evolution.
In some cases, a word translates into a phrase. To add these
words to a vocabulary, we split the phrase into separate words
and equally redistribute the probability associated with the
phrase to these separate words.
Second, as the topic similarity measure is based on word
embeddings ( [33]), we need to know all the words across
every newspaper and time span – we create a global vocabulary
set, V. Global vocabulary consists of all the unique English
words across every time span and every newspaper. Now we
can represent each γt, n, d using the global vocabulary. It
might happen that a word that is mentioned in one subset
of data (e.g., cat) might be missing from the other topic (as
it was never mentioned in that particular subset of data). In
that case, we update the vocabulary of the γt, n, d and assign a
probability of 0 to all newly added words. The aligned vectors
can now be used to calculate the similarities between topics.
Further, we stack all γt, n, d into a matrix Γ∈Rp×v,
where pis the total number of topic vectors (across every
time span and newspaper), and vis the length of the global
vocabulary. Γcontains the probabilities of each word in every
discovered inner topic.
Using matrix Γ, we can extract word embeddings, i.e.,
numerical representations of words ( [33]). Each word, Viis
represented as a vector where dimensions correspond to topics
and values correspond to the probability of word Viin each
inner topic (i.e., the i-th column of Γ).
We calculate the topic similarity based on the average
pairwise cosine similarity of the N-top1words in each topic (
[33]).
D. Global Topic Aggregation
To analyze whether newspapers share discussion points over
a specific time span, we look at the topic similarity. If multiple
inner topics are similar enough, we assume they share similar
contexts. The similarity is calculated between each pair of
topics (produced by all newspapers over the same time span).
We cluster inner topics with the use of the Hierarchical Cluster
Analysis (HCA) with Ward’s linkage function ( [34]).
If the similarity between topics is above a certain threshold,
the HCA model clusters topics together. However, we do not
have any prior knowledge of the optimal threshold value. Thus,
we vary the threshold and look at the quality of the formed
clusters. We use the Silhouette method ( [35]) as a proxy for
the clustering quality. This method estimates whether topics
1N= 10 for Gasoline and Telephone; N= 15 for Iron

7
Algorithm 1 Global Topic Aggregation
Γ∈Rp×vis a matrix containing all discovered γt, n, d and pis a total number of topics
A= distance(Γi,Γj)∀i, j ∈ {1,2,3, ..., p}▷A ∈ Rp×pis a distance matrix
for t= 1 : Tdo
At= subset(A, t)▷Atcontains only between topics of time spans t
thrt= Silhouette(Ward(At))
Vt= Ward(At, thrt)▷Vtcontains sets of similar inner topics
νt←AverageSimilarTopics(Vt,V)▷νtcontain representations of global topics
end for
˜
V= stack(νt∀t∈ {1,2..t})
are closer to the members of their own clusters or vice versa.
For each time span, we find a separate optimal threshold value.
To make clusters comparable, we create cluster representa-
tions by averaging the representations of inner topics that end
up in the same cluster (i.e., the average of the corresponding
rows in Γ). We further refer to those as global topics.
The vectors associated with global topics are stacked into
another matrix ˜
Γ∈Rg×v, where gis the total number of
global topics. The representation of a word, Vi, is now based
on the matrix of the global topics, ˜
Γ(i.e., i-th columns, as in
the case with the Γ).
E. Temporal evolution of topics
We are interested to see how topics change through time
– do they disappear, split into multiple discourses, or stay
unchanged, etc. To examine the evolution of global topics,
we look at the similarities between global topics between
the adjacent time spans, tand t+ 1 (i.e., between topics
of different time spans). We calculate similarities based on
the above-mentioned average pairwise cosine similarity – this
time, we use word embeddings from ˜
Γ. We draw connections
between the topics of the adjacent time spans if their similarity
is above a certain threshold, t. beykikhoshk2018discovering
suggests setting the threshold based on the n-th quantile of the
cumulative distribution of similarity scores. When we estimate
similarities between topics of every pair of t(current) and t+1
(next) time spans. We order the scores, find the 90-th quantile
of the cumulative distribution, and draw arrows between the
pair of topics only if their similarity is higher than the 90-th
quantile 2.
Due to the multi-source nature of the data, our algorithm
might capture some noise. To substantiate the results, we
manually inspect and correct the noisy output of the algorithm.
First, we manually inspect the connection between topics if the
similarity falls within the 85-th and 90-th quantile. We draw
the arrow if the topics share at least one top word. Second,
we remove global topics that consist only of one newspaper.
We also remove topics if the values of the top ten words (in
˜
Γ) are below 0.033. We then manually inspect topics if the
values of the top twenty words (in ˜
Γ) are below 0.05. This
procedure helps to remove topics lacking consistency (such as
this topic with the following set of the top ten words: leave,
world, think, time, know, look, life, people, man, want).
2we decided on the quantile by manually inspecting graphs
3we decided on the threshold by manually inspecting the results
Based on the incoming and outgoing arrows, the life of the
global topics can progress in several ways: birth, evolution,
split, merge, or death. It signifies how public attention and
ideas are refined or transformed ( [36]). The birth of a topic
is characterized by the absence of the incoming arrows - no
topic from the previous time span has a similar context. The
death of the topic would be the reverse of this case – no topics
in the future share a similar context.
If a topic has only one outgoing arrow – it evolves. The topic
does not undergo a drastic change. If a topic has multiple out-
coming arrows - it splits. The successors reuse similar words
and context, but it also involves new words, e.g., the context
surrounding these words changes. If a topic has multiple
incoming connections – its ancestors merge. The context of
the ancestors significantly overlaps. If a topic only has one
arrow with a rounded end, the topic dies and does not evolve
semantically.
VIII. RES ULTS A ND DISCUSSION
After applying our five-step pipeline, and in dialogue with
Fern´
andez Fern´
andez and Savcisens [1] we use three different
metrics in the interpretation of our data analysis: diversifica-
tion, attention, and geography. We are interested in observ-
ing whether topics become more diverse or simplified over
time, showing incremental rates of polarity or agreement, and
therefore seeking to analyze the plausible origins of a shared
Western voice in technological related discourses as early as
two hundred years ago (and by extension observing the agency
of technology as a trigger of information homogenization
and cultural fattening). To measure topic diversification or
simplification, we use as a proxy both the labels of the
topics (that we manually annotate) as well as broader semantic
categories that we implement to create a second classification
of topics qualitatively (and we use same colors inside the boxes
of the topics to indicate equivalent subject matters). We also
quantify which topics receive the highest and lowest rates of
attention by counting the number of represented newspapers as
we seek to observe conflict-affinity trends over time. Finally,
we are interested in measuring the geographic distribution of
newspapers present in each topic, as we wonder whether it is
possible to detect consistent trends of cultural diversity influ-
encing information behaviour and whether changing political
landscapes (i.e. the First and Second World Wars and the
interwar period) may have any effect on trends of information
affinity.

8
Fig. 3. Data Analysis of Telephone
Fig. 4. Data Analysis of Gasoline
A. Telephone
Figure 3 shows the historical evolution of discourses related
to the key term telephone as recorded in our corpus. Our

9
observational time covers 1870-1930, as those are the years
where we could find documents containing the word telephone.
Following the same method as Fern´
andez Fern´
andez and
Savcisens [1], we use boxes to represent global clusters of
topics. Each box includes semantically similar words that we
have grouped in the fourth step of our pipeline using word
embeddings on the English translation of the multilingual
topics that PAM outputted. We provide information of each
newspaper represented in each decade and topic using small
coloured squares at the bottom of each box (topic) and on
top of each date (decade), matching a colour-legend that we
include at each figure. We also gather topics qualitatively
into semantically similar categories (i.e. real estate, politics),
and we indicate this by colouring the background of each
box using the same tone. We depict the connections that the
directed graph calculates using arrows, and we explain arrow
representation (types of connection) in a legend. Additionally,
we represent the number of distinct inner topics in each cluster
by adding a line of dots above each box. Topic clusters that
suffered from under-fitting and therefore included too many
semantically different inner topics to assign a coherent label
were manually removed. We provide similar figures containing
the same information for all our selected three key terms.
Just to provide a reading guide to understand how to
interpret our figures using one column as an example (again,
in dialogue with Fern´
andez Fern´
andez and Savcisens [1]),
in the time-spam 1870-1890 (first column in Fig. 3. Data
Analysis of Telephone), it is possible to observe ten different
topics (boxes): crime (two times), military, domestic service,
entertainment, politics (two times), ship industry (two times),
and finance. However, we (subjectively) group those ten topics
into seven different semantic categories that we showcase by
colouring the boxes: 1. politics (grey), includes topics military
and politics (twice); 2. crime (green), includes the two crime
topics; 3. real estate (lilac), includes the domestic service
topic; 4. entertainment (lime green), includes the entertainment
topic; 5. ship industry (orange), includes the two ship industry
topics; and 6. finance (blue), includes the finance topic. We
will use these broad semantic categories (and colours) in the
rest of the time-spans in all our data visualizations of our
three key-terms. In this time-spam (telephone, 1870-1890),
the two topics shared by the biggest number of newspapers
are finance and domestic service (that include four-out-of-five
of the newspapers included in this study: Neue Hamburger
Zeitung, El Imparcial, The New York Herald and La Stampa.
The two topics that show the lowest affinity across newspapers
are sports (only mentioned by one newspaper) are politics (Le
Figaro) and ship industry (Neue Hamburger Zeitung).
Let’s now proceed to the analysis of telephone under the
three different criteria of diversification, attention, and geog-
raphy. In terms of diversification, it is possible to observe a
clear trend of information simplification coinciding with the
climax of the Second Industrial Revolution around the decades
of 1890 and 1900, followed by a progressive fragmentation in
the next two decades matching the First World War (1910
decade) and the interwar Period (1920 decade), ending in yet
another simplification in the 1930 decade. We observe very
little variation of semantic categories over time (seven in total):
law and order (grey), domestic service (lilac), entertainment
(lime green), ship industry (orange), finance (blue), education
(yellow), and First World War (orange). With the exception of
education and First World War (both appear only in the 1910
decade), the rest of the topics are repeated across all decades.
We interpret this uniformity as an indication of the similarity
of the social impact of this technology (the telephone) in terms
of information behaviour across our selection of multilingual
newspapers.
While we observe how different topics (i.e. domestic service
or real estate) show diverse geographic clustering patterns
(sometimes all newspapers appear represented, sometimes
only two, and sometimes only one), we do not notice signif-
icant semantic differences across topics, indicating the highly
homogeneous cultural effect that this technology had across
the press of diverse societies in that time-frame. Interestingly,
we do not observe any geographic patterns of behaviour (i.e.
a Southern European cluster or an English speaking one), and
we also do not note any historical variations, even though
our selection of countries sided at very different political
locations during the First and Second World Wars. The only
interesting aspect that we see would be the clustering of
Neuer Hamburger Zeitung and The New York Herald in ship
industry related topics, as those two are the only newspapers
headquartered in cities nearby the sea.
In terms of attention, we note five topics that show four-
out-of-five newspapers representation: domestic service and
finance in 1870, politics both in 1920 and in 1930, and
finance in 1870. These results are quite logic, as those are four
central semantic categories that are constantly present across
our analysis, yet the time distribution patterns contradict the
results found by Fern´
andez Fern´
andez and Savcisens [1] in
contemporary datasets. In there, they noticed a tendency of
low-clustering in the first time spans of their study (1999-2003,
2004-2008), followed by an increasing presence of newspapers
representation towards the end (2009-2013, 2014-2018).
B. Gasoline
Gasoline shows very similar results as telephone does across
our three different analysis criteria (diversification, geography,
and attention). While our observational time is wider (now it
covers 1850 to 1930, instead of 1870-1930 as telephone did),
we observe a very similar trend of information simplification
around 1890 and 1900, a fragmentation around 1910-1920, and
another simplification in 1930. The only noticeable difference
would be a semantic fragmentation around the decades of 1870
and 1880 (that, as we will explain later on, overlaps with the
information behaviour of iron).
Interestingly, topics are very similar to telephone, and we
also find the semantic categories (that we have manually
labelled) ship industry (orange), politics (grey), crime (green),
entertainment (lime green), finance (blue), and real estate
(lilac). On top of those, we detect drug industry (red), trans-
port (fuchsia), and Gold Rush (purple). We additionally note
mentions to the First World War in the 1910 decade, but also a
report of the Franco-Prussian War in 1870, as well as another
mention of war in 1920. We infer that gasoline was used in

10
Fig. 5. Data Analysis of Iron
a military context, and that is why it appears more frequently
in conflict-related semantic scenarios than telephone. We also
observe a great uniformity in topic distribution: as it happened
with telephone, the semantic categories of finance, real estate,
politics, and entertainment appear consistently across decades.
Interestingly, we note how drug industry only appears during
the first half of our observational time (1850-1880), and
transport only during the more contemporary decades (1910-
1920), therefore showing the real life evolution of the uses of
gasoline across countries. Similarly and as we noticed in our
analysis of telephone, there is an outlier topic appearing in
1910: Gold Rush (in telephone, it was education).
In terms of geographic diversity, we do not observe any
consistent trends (with the exception of ship industry, that still
clusters The New York Herald and Neue Hamburger Zeitung.
In our analysis of attention, we do observe remarkably similar
trends as in telephone. There are four four-out-of-five topics:
Finance (1920 and 1930), Real Estate (1920), and Politics
(1930), that are exactly the same ones as in telephone. The
only noticeable difference is the historic distribution of these
topics: in the case of gasoline they appear towards the end
of the observational time, while in the case of telephone,
as explained, they appear both at the beginning and at the
end. Unlike in telephone, the semantic complexity of the
context in which gasoline appears triggers the emergence
of many more topics, and that is why we see many more
individual topics overall (and this is a trend that we also find
in iron). However, the broad semantic categories (that, again,
we manually label) remain quite stable over our observational
time and across topics, making us speculate with the idea of
a shared technological experience that can be detected across
different multilingual historic newspapers.
C. Iron
Iron shows a remarkably similar behaviour to gasoline, and
also very similar trends to telephone, in both cases across
our three different metrics (diversification, geography, and
attention).
In terms of diversification, we notice an almost symmetric
trend as in gasoline: a fragmentation of information around
the decades of 1870-1880 followed by a simplification around
the decades of 1890-1900 coinciding with the climax of the
Second Industrial Revolution, and another wave of fragmenta-
tion coinciding with the First World War and Interwar periods.
The most noticeable difference would be a fragmentation of
topics in 1930 (against the simplification found in this decade
in telephone and gasoline).
Topics are very similar to telephone, and almost identical
to gasoline: we also find the general semantic categories ship
industry (orange), politics (grey), crime (green), entertainment
(lime green), finance (blue), and real estate (lilac) appearing
uniformingly across the entire observational time (and, again,
those appear both in gasoline and telephone also during the
whole observational time). On the top of those, we also find
drug industry (red), transport (fuchsia), labour (forest green),
and education (yellow). The war topics now proliferate, and
we find mentions to the First World War in the 1910 decade,
to the Franco-Prussian War in 1870, to the Second World
War in 1930, and to some other unknown conflict in 1890.
We also deduct, as we did in the case of gasoline, that this
term was commonly used in a military context, and that is
why it appears more frequently than in the other two terms.
Very interestingly, we note how drug industry mirrors the
topic behaviour in gasoline and only appears during the first
half of our observational time (1830-1880), and transport
more frequently during the more contemporary decades (1910-
1920), although in this case it also appears during the first
decade of our observational time (1830). While telephone and
gasoline displayed the outliers gold rush and education in
1910, iron does not, but it shows the topic labour in 1890
and in 1920, as well as the topic of education in 1930,
therefore behaving semantically slightly differently (yet still
quite similar to the other key terms).

11
In terms of geography, we do not observe any significant
trends other than The New York Herald and Neuer Ham-
burger Zeitung clustering in the shipping industry semantic
category. However, in terms of attention, we do observe some
differences. We see one full representation topic (that contains
five-out-of-five newspapers): labour (1920). We also notice
two four-out-of-five topics: transport (1910) and war (1910).
Therefore, while the temporal distribution is similar to gasoline
(more newspaper representation towards the more contempo-
rary times), the topics are different (let’s remember than in the
case of telephone and gasoline, major representation topics
(five-out-of-five or four-out-of-five newspapers represented)
were finance, real estate, and politics).
IX. LIMITATIONS
Since computation is used to analyse large amounts of
digitised data, there are some limitations to the obtained
results.
Firstly, the data was digitised using OCR, which does not
yield a perfect result. Indeed, especially in the case of the
Neue Hamburger Zeitung and El Imparcial, the quality of the
OCR strongly limits what can be achieved with the data. The
newspaper articles are also incomplete: they do not span the
entire time frame evenly. This leads to gaps in our analysis
for certain newspapers.
Secondly, most of the newspapers did not digitise their
data article-by-article, but rather page-by-page or even issue-
by-issue. An experimental pipeline was created to try and
split these documents correctly, but it is not perfect. Since
different articles touch vastly different topics, not separating
them correctly can confuse the topic modelling later-on.
Thirdly, the chosen technologies do not have the same
lifetime: the telephone was only invented in the late 1870’s,
whilst gasoline and iron were being used since the beginning
of the corpus (1850 and 1830 respectively). This can make
comparison between results more difficult.
Fourthly, our method presents some limitations when it
comes to analyzing technologically related rhetorics. While
we do believe that our corpus is a good medium of analysis
wherein to observe how different countries encode techno-
logically related discourses, our method discriminates a con-
siderable amount of relevant information, as there are several
instances in our pipeline (such as step three Ward Hierarchical
Clustering, and step four directed graph) that are specifically
designed to only select words with the highest rates of se-
mantic similarity across countries (and by words we mean the
English translations of the multilingual words belonging to the
Pachinko Allocation Topic Modelling Algorithm that we im-
plemented in step one of our pipeline). That means that, while
we are able to find a significant amount of shared discourses
across newspapers (therefore clearly indicating how these
technologies had a similar social impact across countries),
our method is not designed to grasp cultured minoritarian
discourses. We believe that the fact that the majority of the
overlapping topics across papers belong to the semantic fields
of politics, finance, or entertainment, is a clear side effect of
our method’s inner-working (as those tend to be common-place
themes frequently reported by newspapers across countries).
Yet the high homogeneity of our data analysis in these realms
confirms our hypothesis regarding the agency of technology
as a trigger of information homogeneity.
Fifthly, it is also relevant to mention that newspapers
are commodified objects that are designed to be sold for
profit. While newspapers of record tend to report relevant
historic events independently of their respective countries of
origin, they do also provide some format-specific information
about themes such as finance and stock markets, local and
international politics, crime, or weather forecast. In summary:
they report a very specific segment of reality that shapes the
way in which they frame information (and more concretely,
technologically related discourses). However, and as our data
analysis shows, the amount of overlapping information across
all publications is relevantly high, once again showcasing the
social impact of technology as a catalyst of cultural flattening.
Finally, and as mentioned, our corpus has some relevant
data gaps, inevitably impacting our data analysis and thesis
formulation.
X. CLO SE R EA DI NG O F NE WS PAPE R SE CT IO NS A ND
SELECTED ARTICLES
To have a better understanding of our dataset and to what ex-
tent our big data computational analysis is a suitable alternative
(or complement) of traditional hermeneutics, we have decided
to implement a mix-methods approach by incorporating a close
reading analysis of, firstly, a randomized selected number of
newspapers where we closely inspect different sections (i.e.
finance, politics, entertainment...), and secondly, a random
sample of articles containing our target key terms.
1) Newspapers sections: We are curious to analyze whether
our selection of historic multilingual newspapers are compa-
rable objects of analysis among themselves as we initially
suspected that different cultural media traditions were more
nuanced during our observational time than nowadays. We
are specifically interested to observe and contrast newspapers
sections (i.e. finance, politics, sports, science, entertainment...)
in our dataset, to ensure that our medium of study (multilingual
historical newspapers) is relevant for our research question.
Thus we have selected one random newspaper per decade
for each newspaper during our observational time, specifically
focusing on doing a close reading on each newspaper sections
and formatting (i.e. article length or tone of the news). We
have used the PDF version of each newspaper available in
different online repositories ((The Biblioth`
eque nationale de
France (BNF) for Le Figaro [37], The Europeana Project for
Neue Hamburger Zeitung [38], the Archivio Storico de La
Stampa [39], the Chronicling America Historical Newspapers
Collection hosted by the Library of Congress [40], and the
Hemeroteca Digital website for El Imparcial [41] as we seek
to inspect newspapers from a material culture perspective, and
being able to observe the original formatting of our sources is
much more relevant than reading a text data mining version
(i.e. txt files) where some visual aspects of the original outlet
are harder to analyze. We indicate each newspaper consulted,
including its corresponding url, in an appendix.

12
We observe a certain degree of heterogeneity among news-
papers, yet quite contained, as we note how newspapers are
quite homogeneous commodified objects overall. Le Figaro
and The New York Herald are the two news outlets that
present the biggest differences. The New York Herald holds a
typical tabloid format: a high degree of condensed information
into one page, not clear sections and a significant number
of sensationalized news (such as many gruesome details on
news about local crime or an emphasis on political corruption
when talking about local politicians). We note a progressive
streaming of sections as we approach contemporary times (for
example, it is possible to notice entire pages dedicated to
sports or news after the 1900s), but still quite far away from
contemporary notions of newspapers sections. While The New
York Herald reports international and national news (which
is why it is considered as a newspaper of record), it shows
a very strong local flavour by containing an uncommonly
high number of State of New York contemporary references
(advertising, job posts, lost-and-found notices, real state (seek
and wanted) offers, etc). Le Figaro, on the other hand, has
a very strong literary magazine personality. While there is
a very clear evolution towards a tabloid format around the
1890s decade, it still holds certain elements such as article
longer length (each article is almost an opinion peace versus
the telegraphic tabloid style format of The New York Herald),
the presence of chapters of novels, a clear interest on reporting
the artistic and literary scene, and overall a more intellectual
focus. That being said, we observe a very noticeable change
around the 1940s (and more visibly in the 1950s) towards a
tabloid-style outlet.
The Neue Hamburger Zeitung,La Stampa, and El Imparcial
are very similar and can be found right in the middle between
Le Figaro and The New York Herald. They are slightly more
local and less intellectual than Le Figaro, yet they consistently
include chapters from novels and have longer article length
(not as much as Le Figaro, but certainly longer than the typical
tabloid-style shorter format). At the same time, they report
more consistently international news within the realm of the
political interests of each respective countries. For example, in
the case of La Stampa, there is a very big emphasis in reporting
news about the Italian colonial empire in Africa or about
Italy’s foreign policy in countries from the Balkan Region
(more evidently so beginning in the 1920s and onwards).
The Neue Hamburger Zeitung, on the other hand, focuses
more on news about the German colonial empire and German
foreign policy. Anecdotally the Neue Hamburger Zeitung has
two editions: a morning (Morgen Ansgabe) and an evening
one (Abend Ansgabe). We notice how the morning edition is
a more traditional newspaper (less number of pages, longer
articles, more focused on news) and the evening edition is
a tabloid-style newspaper (higher number of pages, shorter
articles, more advertising). We do observe a trend in these
three newspapers towards increasingly becoming a tabloid
style newspaper as we approach contemporary times, yet it
is a very subtle change (specially in the case of the Neue
Hamburger Zeitung). El Imparcial shows a stronger tendency
to report news about Spain and Latin America (and occasion-
ally North Africa) rather than international news, although as
the newspaper approaches the twentieth century these become
more present.
We also notice how some newspapers have a tendency to
report high amounts of local content. For example, The New
York Herald and Neue Hamburger Zeitung (both sea ports)
include a high amount of maritime information: ship tours
advertising, information about ship lines, names of passengers
lists... However, other newspapers such as Le Figaro or El
Imparcial (that, for example, advertise ship lines transporting
mail overseas) also include this information in some decades,
showing how ships were one of the most important transporta-
tion systems of the time.
It is difficult to make strong assertions about newspapers
trends in content or sections as we observe a high degree of
fluidity over time. For example, we notice seasonal variations
in the reported content of the newspapers (i.e. we observe
winter-specific news about ski seasons or winter resorts, and
the same applies to society pages during the summer). As
indicated, historic newspapers during our observational time
did not have contemporary media standards regarding sections,
and therefore, it is possible to observe random information
condensed in every page across all our newspapers (local,
national, international, and random advertising).
That being said, we do note an increasing polarization
of information coinciding with the first and second World
Wars, as well as the interwar period, across our selection
of newspapers. While there is a tendency to observe an
standardization in terms of form (all newspapers gravitate
towards a more nuanced tabloid-format style starting at the
turn of the century and more clearly after the 1920s), there
is a clear tendency towards reporting news reflecting each
country’s political interests in a more aggressive way than in
previous decades. For example, we see many news in Neue
Hamburger Zeitung in the interwar period addressing the topic
of the German economic crisis in the 1920s (Hyperinflation
in the Weimar Republic). We also notice how, during the
First World War, newspapers content varies significantly across
publications due to different political interests.
Consequently, while we note some degree of structural
heterogeneity across our newspapers, those differences balance
each other. As mentioned, some newspapers have a clear
tabloid style (The New York Herald) others a more literary
magazine one (Le Figaro), and some others are in between
(Neue Hamburger Zeitung, La Stampa, El Imparcial). While
some newspapers have a very clear local component by putting
an emphasis on local advertising, crime, or politics (i.e. The
New York Herald), almost all our newspapers include at some
point this kind of information (local real state, lost-and-found
news, job posts...). As mentioned, ships were one of the
preferred means of transportation (human and commercial)
during our observational time. Consequently, while there is a
higher number of ship-related news in newspapers located at
sea ports (Neue Hamburger Zeitung and The New York Times),
all newspapers do report some news about ships. Similarly,
news about religion (i.e. sermons, or religious related news)
also appear more steadily in some publications (The New York
Herald,La Stampa) than in others, yet they appear at some
point in the majority of our newspapers.

13
Therefore, this qualitative approach to the analysis of news-
papers formatting emphasizes the relevance of our data analy-
sis: it complements qualitatively our quantitative observations
(a relatively stable scenario of information homogeneity across
press outlets) that notes how newspapers are not radically
different publications across countries over our observational
time. Consequently, it is quite logic that media frames about
technologically related terms in relatively akin newspapers are
similar. However, we do observe a significant polarization
of newspapers content during the first four decades of the
twentieth century coinciding with the first and second Word
Wars as well as the interwar period. Yet our data analysis
outputs during this time-frame are quite flat. This confirms
our hypothesis about the power of technology as a trigger of
cultural flattening across Western countries: technologically
related media frames have remained relatively stable during
the most turbulent historical periods in recent history.
A. Individual Articles
We are also interested in doing a close reading of a
randomized selection of articles 4containing our key terms
(telephone, gasoline, iron), to assess qualitatively media frames
of technology and the way in which those created an impact
in society (we include in an appendix our selection of articles
and we also include the original text in an online repository).
Generally speaking, we observe that newspaper articles
containing technologically related terms for the most part
report the social use of those technologies, and we observe
three different instances of this phenomenon. Firstly, we note
how the social use of technology is typically embedded in a
larger narrative about some other event. For example, in the
case of iron, we see how Le Figaro reports a trip done by
a European aristocrat (Carlos de Borb´
on y Austria-Este) in
1885 to the Himalayas (that is the main topic of the article).
To reach the peak of the mountain, passengers must use an
iron-made railway that is considered one of the wonders of the
world. Another example would be how La Stampa mentions
in 1920 how, as a result of a post-office strike (that being
the article’s main theme), telephone services were suspended
creating major social chaos. Similarly, the Neue Hamburger
Zeitung reports how in 1921 a storage unit got on fire, yet not
reaching the gasoline tank.
In a second category we note how these technologies appear
in advertising. For example, in the case of telephone, we see
how Le Figaro includes a telephone number in a real state
company advert.
Finally, in a third group, we observe scientific discourses
about the technologies in themselves. For example, La Stampa
provides quite a long article about scientific advances about
gasoline in a car industry context in 1928.
We wrap up this mix-methods approach with the idea
that, as mentioned in the limitations section, our pipeline
is quite efficient in empirically assessing semantic similarity
4Articles used from Le Figaro : [A1]–[A11]
Articles used from the New York Herald : [A12]–[A19]
Articles used from La Stampa : [A20]–[A29]
Articles used from Neue Hamburger Zeitung : [A30]–[A33]
Articles used from El Imparcial : [A34]–[A40]
rates in multilingual corpora (the main thesis of this paper),
yet inevitably, it leaves out some nuances that a qualitative
analysis would reveal. It would be highly interesting to further
decompose quantitatively our dataset by using other method-
ologies such as word embeddings seeking to test how our three
key terms (gasoline, telephone, iron) appear represented across
different newspapers in order to gain a higher understanding
of cultural differences (instead of similarities) of the social
use of these technologies, and complement this analysis with
a qualitative assessment. Similarly, it would also be relevant to
use word embeddings on different thematic areas (i.e. finance,
sports, entertainment) to have a deeper sense of how media
frames encode our key selected terms similarly or differently.
Yet the fact that, again, our data analysis outcomes displays
such a high degree of homogeneity reveals a very similar en-
coding of technology across Western societies during our ob-
servational time necessarily at the article level. This resonates
with our qualitative findings about a relatively similar degree
of homogeneity in newspapers formatting as well as a high
homogeneous content of semantic context (i.e. advertising)
where our technological related terms appear encoded in a
similar way. Consequently, we believe that our mix-methods
approach reinforces our quantitative analysis data outcomes
and our observations about the agency of technology as a
trigger of cultural flattening in media discourses.
XI. CONCLUSION
Our data analysis shows three main findings that appear
consistently across our three selected key terms (telephone,
gasoline, iron): firstly, we detect a trend of information sim-
plification in the 1890 and 1900 decades, coinciding with the
peak of the Second Industrial Revolution in Western Societies.
Secondly, we observe a pattern of semantic fragmentation in
the first two decades of the twentieth century (1910 and 1920),
and in the case of iron, also in 1930, concurring with the First
and Second World Wars, as well as the interwar period. That
being said, we also observe higher rates of agreement (and by
that we mean more topics with either five-out-of-five or four-
out-of-five newspaper representation) also during this time
frame (1910-1930) in both gasoline and iron, and to a certain
extent, also in telephone. Therefore, we notice an increasing
amount of information complexity, but not necessarily of
geographic polarity, which is quite a significant discovery
considering that, during these three decades, our selection of
countries aligned with highly different political views during
the First and Second World Wars as well as during the interwar
period. Thirdly, we notice a remarkable semantic homogeneity
across our three key terms, as there are six semantic categories
that consistently appear in all of them (crime (green), politics
(grey), real estate (lilac), ship industry (orange), finance (blue),
and entertainment (lime green)). Moreover, in the case of iron
and gasoline, they also share the majority of the extra semantic
categories (drug industry (red), and transport (fuchsia)), as
well as their coverage of major military conflicts, which is
nearly identical. Indeed, the only independent topics that are
found in isolation are gold rush in 1910 in the case of gasoline,
and, in the case of iron, religion (1880), and labour (1890

14
and 1920). The topic of education is found both in telephone
(1910) and in iron (1930). As mentioned, our qualitative
analysis reinforces this data-driven findings: we do observe
a high degree of newspapers formatting similarity over time
yet high polarization in content during the first four decades
of the twentieth century. Similarly, we note some patterns in
how technologies are encoded at the article level upon a close
reading of a randomized sample (news reporting the social use
of technologies in three different semantic scenarios: as part
of a longer narration about some other event, mentions about
the use of the technology in itself (i.e. telephone numbers) and
as science-related content).
These results make us speculate with the idea that the
social impact of technology during our observational time
was reflected in press discourses quite homogeneously across
different Eurocentric societies permeating in the realms of
reality where these technologies imprinted lasting effects (i.e.
politics, finance, entertainment, real estate, and ship industry,
shared by all key terms; as well as drug industry, transport,
and education, shared by two-out-of-three key terms). More-
over, we observe a consistent interference of some elements
of the contemporary social fabric at the time (religion and
aristocracy) across different topics and semantic categories,
quite similarly across our three key terms.
We therefore conclude with the idea that, while multilingual
newspapers during the nineteenth and early twentieth century
were slightly more heterogeneous than contemporary news-
papers of record (therefore reflecting the more pronounced
cultural differences across Western societies two hundred years
ago), our mix-methods approach shows the transnational social
cohesion that the Second Industrial Revolution imprinted in
Western societies as recorded by newspapers (that, as men-
tioned, only report a very specific segment of reality). These
findings resonate with existing work on the social impact of
technology by Fern´
andez Fern´
andez and Savcisens ( [1]) in
contemporary newspapers, where the authors show how it is
possible to observe a shared Western voice in sustainability
related discourses over the last twenty years (1999-2018) that
becomes more streamed as we reach contemporary times. This
paper complements their findings by illustrating how that voice
can be traced back to the early stages of the birth of the modern
nation in the mid-nineteenth century, as well as the agency of
technology as a force of identity cohesion in press discourses,
capable of neutralizing the polarizing effects of two World
Wars and an interwar period.
Future lines of research include filtering our dataset with
other key technological terms as well as different subjects
such as politics, finance, or real estate, seeking to test whether
content homogeneity was also present in those semantic realms
or if it was an exclusive phenomenon of technological related
discourses. We are also interested in adding more Western
newspapers from underrepresented regions in our study (i.e.
Scandinavian, central, and low-land countries, Australia and
Canada) as they all hold open source digitized archives of their
major newspapers of record during our observational time. We
are also curious in experimenting with other methodologies
(i.e. word embeddings or sentiment analysis) to further de-
compose tensions between homogeneity or heterogeneity of
information across different news outlets and diverse semantic
fields.
We have created a repository (https://zenodo.org/records/
10657581) where we include scripts, metadata, and the origi-
nal randomized articles used for qualitative assessment match-
ing this paper. We therefore follow FAIR standards.
XII. ACKN OWLEDGEMENTS
This project has received funding from the European
Union’s Horizon 2020 research and innovation programme
under the Marie Sklodowska-Curie (MSC) grant agreement
No 101024996. The authors would like to thank reviewers
for their very useful feedback. The authors would also like to
thank Prof. Jerome Baudry and Prof. Julia Flanders for their
guidance and useful advice. We would like to thank Thomas
Benchetrit for his excellent work on historic newspapers
OCR, carried out during his Master Project in the Spring
Semester 2022. The authors would like to express as well
their gratitude to Clemens Neudecker for his help in the
process of locating and acquiring the Multilingual Historic
Newspapers datasets, as well as to all the authors of the article
”The Corpora They Are a-Changing: a Case Study in Italian
Newspapers” (https://aclanthology.org/2021.lchange-1.3/), for
their generous gesture of sharing with us a very well curated
dataset (and otherwise unavailable) of La Stampa. Addition-
ally, the authors would like to thank very much the Staats- und
Universit¨
atsbibliothek Hamburg Carl von Ossietzky personnel
their help with the Neue Hamburger Zeitung related questions,
and both the Zurich Zentral Library and the University of
Zurich Library personnel for all their help and support.
REFERENCES
[1] E. Fern´
andez Fern´
andez and G. Savcisens, “A sustainable west? analyzing
clusters of public opinion in sustainability western discourses in a col-
lection of multilingual newspapers (1999-2018),” in Digital Humanities
in the Nordic and Baltic Countries 2023. Sustainability, Environment,
Community, Data. Online Conference. CEUR-WS, 2023.
[2] V. Smil, Creating the Twentieth Century: Technical Innovations of 1867-
1914 and Their Lasting Impact. Madrid: Oxford University Press, 2005.
[3] M. Casatells, The Rise of the Network Society. Chichester, West Sussex:
Wiley-Blackwell, 2010.
[4] J. Wajcman, Pressed for Time. The Acceleration of Life in Digital
Capitalism. Chicago: University of Chicago Press, 2014.
[5] A. S. M. T. Bryan Kelly, Dimitris Papanikolaou, “Measuring technologi-
cal innovation over the long run,” American Economic Review: Insights,
vol. 3, no. 3, pp. 303–320, 2021.
[6] P. Stearns, The Industrial Revolution in World History. New York: Taylor
Francis, 2021.
[7] C. M. Cipolla, The Fontana Economic History of Europe. Glasgow:
Fontana/Collins, 1973.
[8] S. King and G. Timmis, Making Sense of the Industrial Revolution.
Manchester: Manchester University Press, 2001.
[9] E. S. Herman and N. Chomsky, Manufacturing Consent. The Political
Economy of the Mass Media. New York: Pantheon Books, 2002.
[10] R. Robertson, The Three Waves of Globalization. A History of a
Developing Global Consciousness. London: Zed Books, 2004.
[11] E. Hobsbawm, The Age of Capital (1848-1875). London: Abacus, 1995.
[12] B. Anderson, Imagined Communities. London: Verso, 2006.
[13] J. B. Vilar, La primera revoluci´
on industrial espa˜
nola (1827-1869).
Madrid: Ediciones Itsmo, 1990.
[14] T. Veblen, Imperial Germany and the Industrial Revolution. Ann Arbor:
The University of Michigan Press, 1966.
[15] G. T. Matteo Gomellini, “The industrialization of italy, 1861–1971,”
2017.

15
[16] A. K. D. W. K. H. D. S. Mariona Coll Ardanuy, Katherine McDonough,
“Resolving places, past and present: toponym resolution in historical
british newspapers using multiple resources,” GIR ’19: Proceedings of
the 13th Workshop on Geographic Information Retrieval., pp. 1–6, 2019.
[17] D. B. M. C. A. E. G. J. H. J. L. K. M. M. R. G. T. D. V. S. D. C. W.
Kaspar Beelen, Ruth Ahnert, “Living with machines: Exploring bias in
the british newspaper archive,” 2019.
[18] K. H. B. M. G. C. Kaspar Beleen, Mariona Coll Ardanuy, “Assessing
the impact of ocr quality on downstream nlp tasks,” Proceedings of the
12th International Conference on Agents and Artificial Intelligence, pp.
484–496, 2020.
[19] R. Kuhn, The Media in Contemporary France. Glasgow: Open
University Press, 2011.
[20] J. L. Crouthamel, Bennett’s New York Herald and the Rise of the Popular
Press,. New York: Syracuse University Press, 1989.
[21] A. B. Magro and L. E. O. Carvajal, Eds., La sociedad madrile ˜
na
durante la Restauraci´
on (1876-1931). Volumen II. El sistema pol´
ıtico de
la Restauraci´
on. El horizonte cultural. Opini´
on y medios de informaci´
on.
Conflicto social y clases trabajadoras. Madrid: Graimo SA, 1989.
[22] E. Saitta, “The transformations of traditional mass media involvement
in the political and electoral process. a case study on political journalism
in france and italy since the 80s.” ECPR Joint Session. Workshop 9:
‘Competitors to Parties in Electoral Politics: The Rise of Non-party
Actors’., 2006.
[23] K. Tornier, Hamburger Pressegeschichte in Zeitungstiteln vom 17 . bis
20. Jahrhundert. Norderstedt: Books on Demand, 2021.
[24] T. Bench, “anxietynews,” https://github.com/ThomasBench/
anxietyNews, 2022.
[25] E. Michelet, “An industrial west? analyzing multilingual newspapers
discourses about technology during the second industrial revolution
(1840-1930),” EPFL, 2023.
[26] W. Li and A. McCallum, “Pachinko allocation: Dag-structured mixture
models of topic correlations,” in Proceedings of the 23rd international
conference on Machine learning, 2006, pp. 577–584.
[27] W. Li, D. Blei, and A. McCallum, “Nonparametric bayes pachinko
allocation,” arXiv preprint arXiv:1206.5270, 2012.
[28] D. Newman, J. H. Lau, K. Grieser, and T. Baldwin, “Automatic eval-
uation of topic coherence,” in Human language technologies: The 2010
annual conference of the North American chapter of the association for
computational linguistics, 2010, pp. 100–108.
[29] E. Cantoni, C. Field, J. Mills Flemming, and E. Ronchetti, “Longitudinal
variable selection by cross-validation in the case of many covariates,”
Statistics in medicine, vol. 26, no. 4, pp. 919–930, 2007.
[30] M. Honnibal and I. Montani, “spaCy 2: Natural language understanding
with Bloom embeddings, convolutional neural networks and incremental
parsing,” 2017, to appear.
[31] bab2min, “Tomotopy,” https://github.com/bab2min/tomotopy, 2019.
[32] G. Savcisens, “Simple topic modelling examples,” https://github.com/
carlomarxdk/topic modelling, 2022.
[33] N. Aletras and M. Stevenson, “Measuring the similarity between au-
tomatically generated topics,” in Proceedings of the 14th Conference of
the European Chapter of the Association for Computational Linguistics,
volume 2: Short Papers, 2014, pp. 22–27.
[34] A. Großwendt, H. R¨
oglin, and M. Schmidt, “Analysis of ward’s method,”
in Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Dis-
crete Algorithms. SIAM, 2019, pp. 2939–2957.
[35] P. J. Rousseeuw, “Silhouettes: a graphical aid to the interpretation and
validation of cluster analysis,” Journal of computational and applied
mathematics, vol. 20, pp. 53–65, 1987.
[36] A. Beykikhoshk, O. Arandjelovi´
c, D. Phung, and S. Venkatesh, “Dis-
covering topic structures of a temporally evolving document corpus,”
Knowledge and Information Systems, vol. 55, pp. 599–632, 2018.
[37] “Biblioth`
eque nationale de france.” [Online]. Available: https://gallica.
bnf.fr/ark:/12148/cb34355551z/date
[38] “he europeana project.” [Online]. Avail-
able: https://www.europeana.eu/en/collections/organisation/
1482250000005967007-state- and-university-library- hamburg-carl-von-ossietzky?
page=1&qa=proxy dc title%3Aneue%5C%20hamburger%5C%
20zeitung
[39] “Archivio storico de la stampa.” [Online]. Available: ttp://www.
archiviolastampa.it/
[40] “Chronicling america historical newspapers collection,
hosted by library of congress.” [Online]. Available:
https://chroniclingamerica.loc.gov/search/pages/results/?state=
&date1=1770&date2=1963&proxtext=new+york+herald&x=0&y=
0&dateFilterType=yearRange&rows=20&searchType=basic
[41] “Hemeroteca digital.” [Online]. Available: https://hemerotecadigital.bne.
es/hd/es/card?sid=188939
APPENDIX
[A1] Le Figaro, October 15th 1854. [Online]. Available: https://gallica.bnf.
fr/ark:/12148/bpt6k269368b
[A2] Le Figaro, 26th of March 1863. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bpt6k270190g.item
[A3] Le Figaro, 22th of August 1876. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bpt6k276067f
[A4] Le Figaro, 18th of September 1888. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bpt6k280521x
[A5] Le Figaro, 27th of October 1896. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bpt6k284179j
[A6] Le Figaro, 26th of April 1906. [Online]. Available: https://gallica.bnf.
fr/ark:/12148/bpt6k287327h
[A7] Le Figaro, 16th of April 1912. [Online]. Available: https://gallica.bnf.
fr/ark:/12148/bpt6k289554k.item
[A8] Le Figaro, 20th of November 1925. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bpt6k2945880
[A9] Le Figaro, 20th of July 1936. [Online]. Available: https://gallica.bnf.
fr/ark:/12148/bpt6k409186m
[A10] Le Figaro, 10th of September 1945. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bd6t563925r
[A11] Le Figaro, 19th of December 1952. [Online]. Available: https:
//gallica.bnf.fr/ark:/12148/bd6t568227q
[A12] The New York Herald, February 3th 1842. [Online]. Available:
https://www.loc.gov/item/sn83030313/1842-02-03/ed-1/
[A13] The New York Herald, May 24th 1853. [Online]. Avail-
able: https://www.loc.gov/resource/sn83030313/1853-05-24/ed-1/?sp=
1&r=-0.277, 1,1.388, 0.545,0
[A14] The New York Herald, September 14th 1868. [Online]. Available:
https://www.loc.gov/item/sn83030313/1868-09-14/ed-1/
[A15] The New York Herald, 3rd of March 1875. [Online]. Available: https:
//www.loc.gov/resource/sn83030313/1875-03-03/ed-1/?st=gallery
[A16] The New York Herald, 12th of January 1891. [Online]. Available:
https://www.loc.gov/item/sn83030313/1891-01-12/ed-1/
[A17] The New York Herald, 26th of March 1906. [Online]. Available: https:
//www.loc.gov/resource/sn83030313/1906-03-21/ed-1/?st=gallery
[A18] The New York Herald, 17th of January 1912. [Online]. Available:
https://www.loc.gov/item/sn83030313/1912-01-17/ed-1/
[A19] The New York Herald, 23rd of January 1920. [Online]. Available:
https://www.loc.gov/item/sn83030313/1920-01-23/ed-1/
[A20] La Stampa, 8th of July 1867. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/
task,search/mod, libera/action,viewer/Itemid,3/page,1/articleid,1282
01 1867 0159 0001 18774389/anews,true/
[A21] La Stampa, 3rd of March 1875. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,1268 01
1875 0062 0001 18637820/anews,true/
[A22] La Stampa, 10th of May 1882. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/
task,search/mod, libera/action,viewer/Itemid,3/page,1/articleid,0015
01 1882 0129 0001 18716325/
[A23] La Stampa, 24th of March 1897. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,1225 01
1897 0083 0001 17986733/anews,true/
[A24] La Stampa, 15th of November 1905. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,0022 01
1905 0317 0001 18201944/anews,true/
[A25] La Stampa, 18th of April 1912. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,1192 01
1912 0108 0001 24272870/
[A26] La Stampa, 28th of November 1927. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,1161 01
1927 0283A 0001 17327602/
[A27] La Stampa, 12th of April 1939. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,1127 01
1939 0087 0001 22637111/

16
[A28] La Stampa, 14th of March 1945. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,0013 01
1945 0073 0001 13912977/anews,true/
[A29] La Stampa, 28th of April 1954. [Online]. Available:
http://www.archiviolastampa.it/component/option,com lastampa/task,
search/mod,libera/action, viewer/Itemid,3/page,1/articleid,0052 01
1954 0101 0001 14426563/
[A30] Neue Hamburger Zeitung, 6th of October 1898.
[Online]. Available: https://www.europeana.eu/en/item/9200338/
BibliographicResource 3000094555194
[A31] Neue Hamburger Zeitung, 19th of September 1906.
[Online]. Available: https://www.europeana.eu/en/item/9200338/
BibliographicResource 3000094626373
[A32] Neue Hamburger Zeitung, 18th of August 1915.
[Online]. Available: https://www.europeana.eu/en/item/9200338/
BibliographicResource 3000094564158
[A33] Neue Hamburger Zeitung, 11th of February 1922.
[Online]. Available: https://www.europeana.eu/en/item/9200338/
BibliographicResource 3000094555396
[A34] El Imparcial, 29th of July 1867. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
51beca61-1997- 4215-b211- 2813de7ab198
[A35] El Imparcial, 24th of November 1875. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
e24031a9-fd47- 425b-bc48- b66efe139390
[A36] El Imparcial, 3rd of March 1882. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
cc8af42d-1550- 4c9b-b05a- 0cecb4ea4646
[A37] El Imparcial, 23rd of November 1898. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
b86b849f-1ec5- 47c2-96fe- 2674871e421e
[A38] El Imparcial, 25th of August 1908. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
c77c4e25-d9d9- 4aa0-a81d- 475dc997521d
[A39] El Imparcial, 26th of November 1917. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
47df68b6-2fd4- 40af-89fb- 3e69a417e923
[A40] El Imparcial, 16th of June 1932. [On-
line]. Available: https://hemerotecadigital.bne.es/hd/es/viewer?id=
462bcd38-1778- 4ec5-b6b5- 285ae4e1cb3e