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26 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
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ABSTRACT
The increasing use of online social networks has given rise to a new kind of relations between residents and
authorities at the municipal level, where residents can more easily than ever engage with administrators and
representatives, participate in open discussions, and may have more direct involvement and inuence on local
affairs. The more direct democracy facilitated by social media tools fascinates communication and political
science researchers. But while most of their attention is drawn to national politics, the municipal arena can be
even more affected by these new means of direct communication. This paper focuses on municipal administra-
tion on Facebook, and analyzes the discourse that has developed between citizens and local administrators
on municipal Facebook pages, using automatic digital tools. The contents of all formal municipal Facebook
pages in Israel were extracted using digital tools, and all posts and comments published on these pages in a
period of six months were analyzed using automatic linguistic analysis tools. The paper presents the prominent
words and expressions, and terms networks and clusters in the formal municipal Facebook pages. The study
discusses the ndings, their implications, and the advantages and limitations of using digital tools to analyze
texts in a digital research eld.
‘Well-Done, Mr. Mayor!’:
Linguistic Analysis of Municipal
Facebook Pages
Nili Steinfeld, Ariel University, Ariel, Israel
Azi Lev-On, Ariel University, Ariel, Israel
Keywords: Big Data, Digital Analysis Tools, Digital Government, Discourse Analysis, Facebook, Linguistic
Analysis, Municipal Government, Social Media
INTRODUCTION
Social networks are used by people around
the globe to engage with other people, groups,
and organizations for diverse purposes. Among
other themes, users discuss politics, make
statements, promote causes and ideas, and try
to influence agendas and decisions. These new
means of communication enable citizens to
directly contact representatives and officials in
a simple and immediate manner.
This novel phenomenon creates a new
field of research that attracts the attention of
scholars of communication and political sci-
ence. The interactions between citizen-users
and government officials can be studied from
a variety of perspectives to learn who takes
part in these interactions, the content that is
communicated, and its perceived impact. In
the present study we focus on the content of
conversations published on official city pages,
DOI: 10.4018/ijepr.2015040102
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International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 27
and using digital linguistic analysis methods we
look at the different themes that are manifested
in these online municipal public spheres.
Municipal Government Online
While most research on the impact of social me-
dia on politics focuses on politics at the national
level, local governance gets much less attention
(Medaglia, 2012). Studies demonstrate that the
scope and complexity of municipal Facebook
usage are steadily improving, and Facebook is
gradually becoming an essential medium for
communication between municipalities and
citizens in Europe and the US (Bonsón, Torres,
Royo, & Flores, 2012; Norris & Reddick, 2013;
Mossberger, 2013).
Still, the scope of diffusion of e-govern-
ment, and specifically of media arenas initiated
by local authorities, are not uniform: Local
authorities have adopted e-government and
social media at different times and have been
using them on different scales and levels of
sophistication. The most important predictor
of diffusion of e-government (and specifically
Facebook usage) has been found to be munici-
pality size, which influences not only media
adoption but also the scope of usage. Municipal
websites and Facebook pages of large cities are
established earlier, and attract significantly more
activity than those of small cities (Ahn, 2011;
Moon, 2002; Norris & Reddick, 2013). Among
the additional variables that predict usage are
population income and education levels (Red-
dick & Norris, 2013).
A recurrent finding in e-government stud-
ies is that municipality websites place greater
weight on static contents, such as tenders and
information on municipal activities, with much
less emphasis on interactive contents (Moss-
berger, 2013; Musso, Weare & Hale, 2000;
Norris & Reddick, 2013; Scott, 2006). The static
character of municipality website communica-
tions is apparently reproduced in municipality
Facebook pages, despite the inherently interac-
tive character of Facebook. Municipalities tend
to disregard the transactional potential of social
media, choosing instead to post informational
materials that also appear on other, more tradi-
tional, media (Graham & Avery, 2013; Lovari &
Parisi, 2012; Oliveira & Welch, 2013). Several
studies illustrate that municipalities rather than
citizens are the dominant actors in uploading
content to municipal websites (Graham &
Avery, 2013; Hofmann, Beverungen, Räckers
& Becker, 2013; Magnusson, Bellström &
Thoren, 2012).
While most studies of municipal social
media focus on mapping and characterizing
which cities are more likely to embed online
social media, engage with citizens, and pro-
mote e-participation, little research has been
done on the content being posted on municipal
administrations’ social platforms. In the three
studies familiar to us at the time of writing,
Lovari & Parisi (2012) analyzed the text in
the Facebook pages of four Italian provincial
capitals (and found that the leading content
categories were event promotions, information
about public services and opportunities; alerts
about emergencies and disservices; and calls
for civic participation); Hand & Ching (2011)
analyzed the text in the Facebook pages of nine
cities in the Phoenix area (the leading content
categories were administrative and commu-
nity announcements, activity suggestions and
more); and Magnusson et al.(2012) analyzed
the text in the Facebook page of Karlstad,
arguably a “Facebook leader” among Swedish
municipalities (the leading content categories
were self-promotion of the municipality, and
promotion of events).
In spite of their significance, these studies
well demonstrate the drawbacks of relying on
manual content analysis methods, which are
limited in terms of the volume of the data studied.
Applying Digital Tools
for the Study of Digital
Municipal Behavior
What can we learn from studying municipal
Facebook pages and how can the findings be
utilized for improvement of service given by
municipalities?
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28 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
Smart cities rely on digital technologies
to improve the quality of life and wellbeing of
their citizens. They monitor different systems
and aspects of life in order to improve their
performance and effectiveness (Hollands, 2008;
Schaffers, Komninos, Pallot, Trousse, Nilsson,
& Oliveira, 2011). In that sense, municipal Face-
book pages are useful sources of information,
where citizens act as a sort of sensors, helping
in the process of e-planning by raising important
issues to be discussed and handled, and help-
ing the city to realize the problems and issues
that need to be addressed. Input from citizens
can be analyzed so that cities know in what
aspects citizens are content, and what needs
improvement and additional care. If citizens
are discontent with a specific topic, may it be
parking problems, the state of classrooms and
school buildings or other topics- that input can
be used to decide what areas should be addressed
and how resources and budgets should be used.
How should municipal pages on Facebook
be analyzed?
Internet researchers are involved in recent
years in debates over the preferred method to
study online phenomena, as more researchers
adopt computational research methods and
digital tools for their research. Arguments for
and against the move to “Big Data” research
methods are diverse. Some argue that digital
objects and phenomena that are “natively digi-
tal” are best studied by natively digital methods
and tools (Herring, 2009; Rogers, 2009). These
tools allow an unprecedented scale and depth of
analysis, specifically in social science research
(Giles, 2012; Lazer et al, 2009). They enable the
aggregation of data from a variety of sources
such as different social networks or various
online platforms, repurposing and reformat-
ting unstructured data of different types in a
way that enables the analysis and processing
of these once “messy” data. Thus, in short, a
digital approach to digital social research can
reveal more than traditional methods may, and
enable researchers to see the broad picture more
clearly (Boyd and Crawford, 2012; Cioffi-
Revilla, 2010; Lazer et al, 2009).
Critics of these new methods of research
state the need for a more theory-guided research,
where in many cases the research outlines what
was found, but lacks some necessary grounded
social science theory as its basis (Boyd and
Crawford, 2012; Snijders, Matzat & Reips,
2012). The reliance on commercial platforms
that operate as black boxes for the gathering
and analysis of datasets, and the necessary
process of “cleaning” the data, can cause bias
and sometimes prevent researchers from ac-
counting for the representativeness and accuracy
of the data (Bollier and Firestone, 2010; Boyd
and Crawford, 2012). A main question to be
asked regarding automated, computer-mediated
analysis is: What kind of questions can this
type of research answer, and where does it fail?
In the current study, the use of automatic
tools for the extraction and analysis of municipal
Facebook pages was chosen due to these tools
and methods’ unique capabilities and applica-
tions. As this is the first study to examine interac-
tions between citizen-users and municipalities
on Facebook using automatic tools, an explor-
atory approach is appropriate. Since these are
public pages, hosting a discourse that is public
and political in nature, the use of digital tools for
scraping and analyzing the pages can be done
without limitations – technical or ethical – on
the data being analyzed, and enables large-scale
research that allows the researchers to include
all pages and all posts for a given period of time
without having to sample the data analyzed. An
approach that can supply preliminary insights
on a massive volume of data from interactions
between citizens and municipalities on formal
pages, “from a bird’s eye view”, which manual
analysis methods will not be able to achieve.
In addition, as some of these tools are based on
open source software, they allow researchers
using them to study their algorithms and follow
their logic, and by that compensate for the lack
of transparency of the platforms of which data
is obtained, to some degree.
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International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 29
RESEARCH QUESTIONS
Facebook is extremely popular in Israel, and
the country has one of the highest rates of
Facebook usage in the world (ComScore, 2011).
Therefore, Facebook, as the most relevant so-
cial media platform for citizens who wish to
engage with their local authority, is the focus
of this study. This study aims at conducting a
preliminary analysis of posts and comments
published by municipal officials and by citizens
in formal municipal pages on Facebook, to track
prominent words and terms, and to extract the
central topics discussed on these pages. This
kind of analysis can shed light on what interests
citizens most when engaging with their local
representatives, what aspects of city life are
being addressed in the pages- information that
can help cities become “smarter”: bettering the
life of their citizens by addressing and handling
with issues that occupy them most:
RQ1: What are the prominent words and terms
in the municipal Facebook pages?
RQ2: Are there prominent topics that occupy
the users of these pages, according to which
municipal pages can be categorized and
clustered?
In addition, we were interested in compar-
ing texts posted by officials (the pages them-
selves) to posts by citizens (users) and seeing
what differences in topics and in the use of
language we can spot:
RQ3: In what way are posts initiated by mu-
nicipal government pages different than
posts initiated by citizens? Are the topics
that interest citizens significantly different
than those that the city discusses, do the
posts initiated by municipal government
pages use a distinctively more formal and
official language form than the language
used by citizens, or do citizens use a for-
mal language when interacting with cities
as well?
An additional comparison was made on
the basis of the city’s socio-economic status:
RQ4: Are there differences in language use in
pages of cities ranked higher on a socio-
economic scale, compared to middle and
lower-ranked cities? Are the topics of
posts different between higher and lower-
ranked cities?
METHODOLOGY
Municipal administration in Israel is composed
of three levels: cities (in general, municipali-
ties with over 20,000 residents), local councils
(in general, municipalities with 2,000-20,000
residents), and regional councils – generally
comprised of a number of communities with
less than 2,000 residents each (Central Bureau
of Statistics, 2012). In this study, we focused
on cities alone, which are the more prominent
and central type of local authorities.
A list of all 75 cities in Israel was compiled
based on data from the Israel Central Bureau of
Statistics website (Central Bureau of Statistics,
2011). In order to find the formal Facebook page
of each city, we searched the relevant pages in
the website of the Union of Local Authorities in
Israel and of the Israel Ministry of the Interior,
as well as in the cities’ webpages, using a pre-
compiled list. Using Google’s search engine and
Facebook, we searched by the name of the city
in Hebrew, Arabic, and English, which are the
three formal languages in Israel. The search in
Arabic found no relevant results. Three pages
were found using an English search and the rest
were found through the Hebrew search.
One municipality uses a personal profile
instead of a formal page and was excluded in
the study, due to Facebook’s policy to disallow
the use of personal profiles by formal organiza-
tions, which sometimes results in these profiles
being disabled by Facebook.
A total of 41 Facebook pages were found
and included in the study. For all cities, socio-
demographic data was collected from the Israel
Central Bureau of Statistics website (Central
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30 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
Bureau of Statistics, 2011). The data includes
which socio-economic cluster the city belongs
to on a scale of 1 (lowest ranking) to 10 (highest
ranking). The classification of cities is based
on the population’s general socio-economic
level, measured by a combination of variables
in the categories of demographics, education,
employment, and standard of living (Central
Bureau of Statistics, 2012).
After mapping the municipal Facebook
pages, we used Netvizz, a Facebook appli-
cation created at Digital Methods Initiative
labs (https://apps.facebook.com/netvizz)1 that
scrapes data from Facebook pages and groups.
The tool generates comma-delimited files con-
taining the texts of all posts and all comments
published on a page or a group, and relevant
metadata such as number of likes, comments
and shares made to the post, publication date,
whether the post was published by the page
managers or by users etc. The application was
used to gather all posts published on the official
municipal pages, by either the pages or other
users, and all engagement measurements per
each post. Posts’ comments were also obtained
from the Facebook pages. In addition, the tool
generates a network file summarizing all of
the engagements between users and posts on
the page.
We used Netvizz to create and summarize
the pages’ activity for a period of six months,
between October 22, 2012 and April 22, 2013,
when the data was extracted. We used all of
the posts and comments published by either
the pages or users during that period in order
to avoid sampling bias, and to include all of
the interactions on these pages during these
six months. Some of the pages were created
during that period. In these cases, we analyze
all posts – from the time of the page creation
until April 22, 2013.
After preparing the data, we used automatic
linguistic analysis tools that provided informa-
tion regarding the use and frequencies of words
and terms in the posts and comments texts,
and allowed us to come to basic, preliminary
conclusions regarding the type of discourse that
is formed on these pages. The analysis of the
frequency of words and terms (also referred to as
text-level concepts, or themes; see Diesner and
Carley, 2005) is a common method in automated
text analysis, based on the proposition that the
frequency of words and themes can indicate the
prominence of concepts in the text and the inter-
est in these themes by the producer of the text
(Popping, 2000; Schutz and Buitelaar, 2005).
We used Corsis (formerly Tenka Text), an
open-source corpus analysis class library, to gen-
erate word frequency data (http://sourceforge.
net/projects/corsis/).2 The tool gets as input plain
text, and returns a list of all words in the text and
their frequency. We entered the tool all of the
posts and comments texts in order to receive a
list of all prominent words in the entire corpus.
Cortext Manager, a textual corpora analysis tool,
was used to extract frequent terms from the
corpus and conversational clusters (http://www.
cortext.net).3 The tool receives files containing
texts, parses them and enables to search and
create a list of common terms (by searching for
frequent words that are repeatedly pairing with
each-other). We uploaded files of all posts texts
at first, and then uploaded separate files for the
texts of users and pages, and texts of cities of
low, medium and high socio-economic status.
RESULTS
A total of 23,768 posts and 71,338 comments
were obtained and analyzed.
Analyzing the Texts of
Posts and Comments
Let us start with addressing RQ1, regarding the
prominent words and terms in the municipal
Facebook pages.
Word frequency analysis of all of the
comment and post texts revealed that there is
a great deal of self-reference in the texts. The
word “I” (“Ani” In Hebrew) was very prominent
and repeated 15,366 times in the texts, being
number 8 on the frequency list. Also, “To me”
(“Li” in Hebrew) repeated 6543 times in the
text, being the 16th most prominent word in the
text. The first third-person word, “He” (“Hu” in
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International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 31
Hebrew), is number 23 on the list and repeated
5394 times in the text. A high frequency of
first-person words suggests that the posts are
usually written from a personal point of view,
and use personal notes. A personal tone suits
the characteristics of the platform and suggests
a use of the social network environment to pro-
mote an informal, direct interaction between the
various speakers on the pages. Unsurprisingly,
prominent in the text are words referring to the
city (11,328, 5067, 4852 and 4630 times for
various versions of the word). The first word
that relates to a group or collective is “For us”
(“Lanu” in Hebrew) and it appears 33rd on
the list (repeating 4712 times in the text). The
texts apparently often consist of questions:
Various question words were also frequent in
the analysis (What- 10505 times and tenth most
frequent, Why- 3908 times, Who- 3487 times,
How much- 3001 times, Whether- 2861times,
How- 2295 times).
Turning to a more comprehensive linguistic
analysis, using Cortext Manager we extracted
the most prominent and frequent terms in the
texts. Terms are extracted by the tool on the
basis of frequencies of words pairing with
each-other in the text.
The most prominent term was “Well done”,
with 2908 occurrences throughout the texts. The
second most prominent term was “The mayor”,
with 2430 occurrences. It seems that the posts
and comments had discussed the municipality
and the mayor, and tended to be more positive
than negative: “Thank you for”, “Thank you
very much”, and “Well done for” were very
frequent in the texts and repeated 1052, 820,
and 331 times, respectively. Greetings are fre-
quent too: Happy holiday repeated 590 times,
Figure 1. Tag cloud of the 100 most frequent words in the posts and comments texts, translated
to English (created using Wordle-http://www.wordle.net/)
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32 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
Good morning- 457 times, Good Shabbos- 388
times. But the texts also had negative comments.
“Shame on you” was a repeating phrase (294
times), and also “Disgusting” (251) and “Just
a disgrace” (189).
From analyzing frequency of terms in the
texts, we can understand some of the concepts
reoccurring on the pages, and even point to
possible trends in the discourse that evolves on
the pages. The pages are used for supporting
and congratulating subjects (may they be the
cities, organizations, or citizens), but are also,
although less frequently, used to complain and
express resentment and dissatisfaction.
Clusters of Prominent Topics
in the Municipal Pages
Next, let us address RQ2, about categories and
clusters of prominent topics in the municipal
pages. Using Cortext Manager Heterogeneous
Mapping script, we created a heterogeneous co-
occurrences network based on direct measures,
which calculates the raw co-occurrence number
between two terms, and ignores the global
distribution of co-occurrences of the two terms
with all other terms in the analysis (http://www.
cortext.net). The use of mapping on the basis of
co-occurrences of terms (or concepts) is a com-
mon method in the field of computer-mediated
text analysis. The underlying assumption of
the use of this method is that co-occurrence of
terms indicates a relation between the terms
(Ohsawa, Benson and Yachida, 1998; Popping,
Figure 2. Tag cloud of the 100 most commot terms extracted by CortextManager, translated to
English (created using Wordle-http://www.wordle.net/)
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International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 33
2000; Rebholz-Schuhman et al., 2007; Zhu and
Porter, 2002). In this study, co-occurrence of
terms means they were used in the same post;
therefore this type of analysis is particularly
useful to gain insight on the relation between
concepts in the posts analyzed. Since we are
interested in co-occurrence of terms in the same
post only, a direct measure was most suitable.
The tool spotted a map of terms clusters in
the texts, created by measuring closeness (i.e.,
co-occurrences) of terms in the texts. Fourteen
clusters were created.
The first cluster contains most of the nega-
tive terms and residents’ complaints: “Doesn’t
make sense”, “I disapprove”, “Disgusting”,
“No-one”, “Just a disgrace”, “Shame on you”,
“We don’t have”, “Just not”. Apparently these
terms co-occur with discussions and terms
related to Tel-Aviv, which was the most promi-
nent term in the cluster (and therefore is the
cluster’s name, given by the program). Tel-Aviv
mayor’s name, Ron Huldai, is also among the
cluster’s terms, and other cities names: “Bat-
Yam”, “Rehovot municipality”, and “Jerusalem
municipality”.
The second cluster seems to be related to
times of emergency. During the period exam-
ined, a military operation in Gaza, called Pillar
of Defense, took place, and the cities of Israel
were attacked with missiles from the Gaza Strip.
The cities’ Facebook pages were a platform for
citizens to be updated and get some answers
regarding ways to defend themselves in case
of emergency. This cluster, evolving around the
terms “The alarm” and “can’t”, contains terms
stating inability: “I can’t” (in male and female
as well as singular and plural forms), “Don’t
know”, “But it’s not”, “It’s really not”, “We
can’t hear”, “What will happen”, “It’s happen-
ing”, “No-one”. There is a sense of confusion
and anxiety that comes from reading the terms,
which suggests that cities’ pages are used by
citizens during emergency times to settle their
confusion and express their need for assistance
and reassurance.
The third cluster deals with issues concern-
ing education, and is composed of different
terms related to schools (“In the schools”, “To
the schools”, “At the Schools”, etc.), and related
terms such as “Ministry of Education “, “The
children”, “The studies”, “Kindergartens”. This
cluster is also prominent, suggesting that a sig-
nificant part of the discourse revolves around
education and that cities’ pages are used to
discuss the educational system in the city and
issues related to education.
The fourth cluster is composed of wishes
and greetings, which were prominent in the
terms list as well. Most prominent are: “Lots of
Health” and “Happy holiday”, and also “Thank
you very much”, “Shabbat Shalom” (Good
Shabbos), “Congratulations”, “Feel better
soon”, and “Birthday”. The use of greetings and
congratulations strengthens the sense of com-
munity in the cities’ pages and the connection
between citizens and the municipality.
The fifth cluster contains terms related
mainly to formal government operations and
emergency practices, and contains the terms:
“Ministry of Environmental Protection”, “Home
Front Command”, “Keep safe”, “Pay attention”,
“All through the city”, “Protected space”, “What
to do”. This cluster points to the use of Facebook
pages as a platform for public announcements.
The sixth cluster is the informative cluster,
revolving around the term “For further details”,
and contains messages on events and terms
such as: “You are invited”, “In the theatre”,
“Entrance is free”, “Sunday”, “Friday”, etc.
This cluster seems to be composed mostly of
comments and posts by the pages themselves,
which use the pages to inform citizens of events
organized by the city and invite them to shows
or other special occasions.
The seventh cluster incorporates most of
the questions posted by users to the pages or to
other users. Terms such as “And what about”,
“What’s up with”, “Until when”, “I wanted to
know”, “What is going on”, etc., compose this
cluster, named “What about” by the program,
and suggests that citizens use the pages to submit
questions to officials regarding events, office
activities, issues and problems they encounter
with the municipality, and other information.
The eighth cluster revolves around the
mayor and the city: “The mayor” appears in
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34 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
many forms (“With the mayor”, “To the mayor”,
“Of the mayor”, etc.), as does “The town”, “The
city”, “The residents of the city”, “The youth”,
“Well done to our residents”, etc.
Cluster nine is the formal town hall
messages, revolving around the terms “The
mayor’s office” and “Public inquiries”. Terms
in this cluster include: “Good day”, “In order
to”, “Please contact”, “Your request has been
forwarded”, “In any case”, “Thank you for your
inquiry”. This cluster represents a more formal
tone used by the pages, usually with regard to
formal applications by citizens, and suggests
that the tones used by the pages vary from in-
formal and personal to formal and representative
according to the issues addressed in the posts.
The tenth cluster is composed of complaints
and questions on a negative formulation: “Why
not”, “What not”, “You don’t answer”, “You’re
not”, etc., and suggests that the pages are also
used for complaining about the cities’ perfor-
mance or other issues.
Cluster eleven gathers terms related to
the celebrations of Independence Day: “In-
dependence day”, “Free of charge”, “State of
Israel”, names of several cities (Kfar Saba,
Ramat Hasharon), and the name of a famous
Israeli singer who performs on many stages on
independence day – Eyal Golan.
Cluster twelve includes terms related to
requests for contact details for further treatment:
“Please forward to us”, “Your phone number”,
“Will look into”, “The subject”, “In a personal
message”, “Personally”, “Contact”, “All the
details”, etc., and suggests that Facebook is
used to submit requests or initiate an interac-
tion with the city, which sometimes evolves to
further interaction on another level of platform
– by phone, in personal messages, or in person.
Cluster thirteen is similar to cluster eight,
and deals with the city and with specific cities
that are prominent in the corpus: “Haifa munici-
pality”, “Be’er Sheva municipality”, “Rishon
Lezion municipality”, “Well done, the city of”,
“The mayor”, etc.
The last cluster incorporates reinforce-
ments and encouragements such as: “Well
done”, “Well done on the initiative”, “Keep
up”, “So much fun”, “Fantastic”, and suggests
the use of Facebook to reinforce subjects, or the
city, for successful events or initiatives, a sort
of thank-you note to express gratitude.
Difference in Text styles:
Among Cities, and between
Cities and Citizens
Moving to comparison of the texts posted by
pages and by users (RQ3), the most prominent
term in both pages’ and users’ posts is “the
mayor”. Other terms that appeared frequently in
both users’ and pages’ posts include “For more
details”, “The school”, “Please note”, “You’re
invited”, and “Independence Day”. The pages’
posts, as expected, use more formal terms and
invite residents to join events (“You’re invited
to come”, “It’s happening”, etc.) and to engage
with the city online (“Give us a Like”, “Go to our
website”, etc.). Users’ posts included greetings
and thanks (“Thank you”, “Well done”, etc.),
personal references (“I want”, “I have”, etc.),
questions and complaints (“Why not”, “What’s
going on”, “This can’t be”, “This doesn’t make
sense”, “I wanted to know if”, “I’m asking”, “I
would appreciate”, etc.). To sum up the com-
parison between users and pages, it seems that
there are similarities between users and pages
in the subjects discussed in their posts. Users
discuss the mayor and schools in a similar
manner as the pages. Interestingly, they use
the pages to inform others – may they be other
citizens or the municipalities themselves, of
events or other issues, a kind of discourse we
would expect pages to engage in, but they are
less informative than the pages. It seems that
the style of pages is more formal, they are more
involved in informing about events, and they
actively try to engage citizens with the city –
offline as well as online. Users, unsurprisingly,
are more personal and use the pages to express
discontent and complain. These conclusions
are preliminary and more in-depth analysis
is needed to fully understand the differences
between users’ and pages’ texts.
When comparing terms frequencies in
comments and posts from pages of cities of
Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 35
different socio-economic ranking (RQ4), we
found in general no big difference in the dis-
course between cities from a lower, medium,
or high socio-economic cluster. Many terms
repeated in the three groups: “Well done” and
“The mayor” are the most prominent in all three
groups, “Happy holiday” appeared in all groups,
“School” and related terms were prominent in
all three groups as well. But it seems like the
tone of the discourse is slightly more negative
as the socio-economic status is higher. Fifteen
of the 300 most frequent terms in pages of cities
that belong to a lower socio-economic cluster
(1-3 out of 10) contained the word “No” or
“Not” (e.g., “Not anymore”, “If not”), while
for cities of a medium socio-economic cluster
(4-6 out of 10) the 300 most frequent terms
contained 21 terms with “No” or “Not”, and
cities of the high socio-economic clusters (7-10
out of 10) contained “No” or “Not” in 40 of the
300 most frequent terms. Also, the term “Just
a disgrace” was frequent in the texts of lower
socio-economic cities. The term “disgusting”
was frequent in the medium socio-economic
group. But both terms, together with “Shame
on you”, were frequent in the higher status
group and were more prominent than in the
lower-ranked groups. Again, these are basic
and general findings that do not tell the entire
complex story, but seem to point to an interesting
trend that can set the stage for a more in-depth
analysis for further examination of what was
discovered by the tools used in the current study.
DISCUSSION
Using automatic linguistic analysis tools, we
were able to come to preliminary conclusions
and get a taste of what posts by citizens and
cities on formal municipal Facebook pages
are about. While looking at word frequencies
only, the depth of analysis was quite limited.
Without knowing the context, frequent words
that were very common, such as “No” or “The”,
had very little meaning for the research. The
prominence of self-reference words, especially
when compared to third-person and group refer-
ence that repeated much less frequently, implies
a tendency to discuss personal matters on these
pages, but without further investigation into the
texts there is no way of knowing the context in
which users refer to themselves in the posts.
Term frequency analysis, however, is
much more comprehensive and enables more
meaningful insights. Here, we were able to spot
several main topics and even the tone of the
message. It seems that, in general, Facebook
pages are a place of reinforcement and posi-
tive attitudes, where citizens and cities use the
platform to congratulate, express gratitude, and
support projects and initiatives. Positive terms
were significantly more prominent and diverse
in the texts than negative terms. The fact that “the
mayor” was such a prominent term suggests,
again, that the discourse tends to be personal
in nature, where posts frequently mention the
mayor and not just the city or council. In ad-
dition, cities frequently encourage citizens to
engage with them on Facebook, suggesting they
like content posted by them and let them know
what they think, and direct citizens to other
online platforms such as the city’s website,
which point to a growing tendency to embrace
the medium and its uses for public relations (for
similar findings, see (Lovari & Parisi, 2012;
Hand & Ching, 2011; Magnusson et al., 2012).
Using the tool’s heterogeneous co-
occurrences network feature we were able to
deepen our analysis and track clusters of terms,
indicating closeness of terms in the texts (terms
that tend to appear in relation to each other),
which enabled us to focus on several topics
and discuss the main trends and issues dealt
with on the pages. We found that city pages
are used for public notification of events at
the municipal level, such as celebrations and
holiday events, and at the national level, such as
emergency drills and wartime notifications (see
Lovari & Parisi, 2012; Hand & Ching, 2011;
Magnusson et al., 2012). The latter were tied
with citizens’ expressions of anxiety, confusion,
and sense of inability. The pages were also used
for discussing issues related to the education
system, and for submitting formal requests to
the municipality. Although not as prominent, a
Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
36 International Journal of E-Planning Research, 4(2), 26-38, April-June 2015
notable number of posts reflected dissatisfaction
and complaints of citizens. The fact that all of
the negative terms were included in one cluster
(meaning they appeared in same texts often),
and that the most prominent term associated
with them was “Tel-Aviv”, accompanied by the
name of the mayor of Tel-Aviv, was unexpected
and especially interesting. Reinforcement of this
finding was found when we compared terms
frequencies and found some evidence that in
the high-ranked cluster, in which Tel-Aviv is the
dominant city, the use of terms that represent
dissatisfaction and negative expression was
more significant.
But here’s where tools and algorithms are
insufficient: In order to understand what makes
high-ranked cities’ residents, and especially
Tel-Aviv residents, more upset then others, to
find out in what context, around which issues,
the citizens of Tel-Aviv and other high-ranked
cities express their anger and antagonism, we
had to go back to the posts themselves. The
tools’ analysis provided us with the key – what
terms to look for, where to search. But in order
to fully understand the basis for the expression of
such criticism, there is no alternative to manual
content analysis. What we found, in a qualita-
tive examination of posts containing negative
expressions, was a variety of issues, with a
dominant presence of posts complaining about
unjust parking tickets. This finding managed to
settle the inscrutability of the former findings
and was actually not surprising, as there is an
on-going public debate among residents and
non-residents around parking problems in Tel-
Aviv. This kind of conclusion is difficult to be
drawn from using automated tools alone. The
tools were proven useful in pointing out general
issues and tones of voice that were prominent in
the posts and comments, but could not replace
manual content analysis for the task of describ-
ing the exact topics discussed on pages, and
the different contexts of using a specific term.
To conclude, we find automated tools for
data extraction, linguistic analysis, and dis-
tinction and visualization of terms networks
highly productive and useful for the purpose of
exploring and discovering uses, discourses, and
interactions in general on municipal Facebook
pages between citizens-users and municipali-
ties-pages. The use of automated tools enables
us to include large scale datasets (in this case-
Facebook posts and comments) and analyze
an entire corpus without having to choose a
sample of texts for analysis. Although manual
analysis can reveal more in-depth patterns and
uses of these pages, using just the automated
tools we were able to sketch a dominant dis-
course, emerging topics that concern citizens
and municipalities, some differences between
users and pages, richer and poorer cities, and get
some clear sense of what occupies citizens in
Israel on the municipal level, and what is being
discussed on these pages out of an entire and
exhaustive corpus of six months of activity on
all municipal Facebook pages in Israel.
These findings can serve cities and deci-
sion makers at the municipal level to better
understand the way social media in general,
and Facebook in particular, is used by citizens
to express gratitude, criticism or their opinions
on events, announcements or other issues at the
municipal level. This platform is more than
just a space for social interactions. In the con-
text of smart cities- it is a crucial data source,
which gathers important inputs relevant to the
performance of the city, and how it is viewed
and accepted by citizens. Understanding what
occupies and interests citizens, what are the
issues around which they express discontent
and what issues they are satisfied with- sets
the ground for improving the service given to
citizens in various domains by the city.
FUTURE RESEARCH
The tools used in this study, and the method
of analysis, can be applied to other domains
and social media platforms, and a comparison
between prominent words and terms on vari-
Copyright © 2015, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
International Journal of E-Planning Research, 4(2), 26-38, April-June 2015 37
ous platforms such as Twitter, Google Plus etc.
can be interesting and may point to differences
in the ways these platforms are being used by
citizens: A comparison of that sort may answer
questions such as: what is the impact of the
unique structure of Twitter twits and the limit
of 140 characters on the use of language and
topics covered? Are twits more focused and on-
topic compared to Facebook posts? Are Twitter
users (who may be very different in character
and in style from Facebook users) occupied
with different issues? and more.
ACKNOWLEDGMENT
The study was supported by the Center for the
Study of New Media, Society and Politics at
Ariel University. The authors thank Valerie
Aronov, Veronika Makogon and Avital Mandel
for their assistance in data collection.
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ENDNOTES
1 We thank the Digital Methods Initiative and
Bernhard Rieder for the use of the tool.
2 We thank the developer, Cetin Sert, for the
use of the tool.
3 We thank the Cortext team and IFRIS for the
use of their tool.
