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The Canadian journal of information and library science - La Revue canadienne des sciences de l’information et de bibliothéconomie (CJILS-RCSIB)
Vol. 47, No. 2 (2024) - Bobcatsss 2024 conference special issue
DOI: 10.5206/cjils-rcsib.v47i2.17633
Conference paper
Subject Analysis, Content Analysis, and Domain Analysis: Concepts,
Methods, and Applications
Tauany Lorena Alves Silva Portella and Gercina Ângela de Lima
Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil
From the perspective of the constant increase in data and information, consider in Library
and Information Science that the correct analysis and representation of the contents of doc-
uments analyzed in specific domains is essential for the retrieval, organization, and dissem-
ination of information. Subject Analysis categorizes topics and details, making it easier to
retrieve relevant information. Domain Analysis studies specific characteristics of a field of
knowledge, comprising terminologies and concepts. Content Analysis identifies and analyzes
textual elements, deepening the understanding of documentary content. This study explores
these analyses’ approaches, techniques, and methodologies, highlighting their often confused
interrelationships, differences, and similarities. To achieve the proposed objective to support
the conceptual and theoretical-methodological discussion on subject analysis, content analysis,
and domain analysis, focusing on their interrelations, differences, and similarities that are
often confused in their concepts and methodologies, the research developed an exploratory and
descriptive approach, a bibliographic survey was carried out in the BRAPCI database, using the
terms "domain analysis", "content analysis" and "content analysis", recovering 134 documents.
Results are efficiently defined and applied to each analysis. These analyses guarantee efficient
information retrieval, which is vital to growing data volume.
Keywords: subject analysis, domain analysis, content analysis, semantic analysis
Introduction
Given the constant increase in data and information, the
correct analysis and representation of document contents and
a specific domain are of the utmost importance for retrieving
and disseminating knowledge. Among the main available ap-
proaches are subject analysis, domain analysis, and content
analysis, techniques used to identify, interpret, and understand
the meaning of document content and knowledge domain.
Subject analysis aims to identify the main subjects in the
text, extracting these concepts to be used in search and fa-
cilitating information retrieval. It allows the identification of
dominant terms for use in classification. Domain analysis also
seeks to identify themes within the text, but it considers the
domain in which it is addressed, considering terminologies,
concepts, and specific relationships within an area.
With a broader approach, content analysis seeks to under-
stand implicit meanings in texts. It can analyze qualitative
and quantitative data and the relationships between terms to
arrive at a more detailed understanding of document content.
In this article, we will explore and compare these three
Correspondence concerning this article should be addressed to
Tauany Lorena Alves Silva Portella: tauany.ufmg@gmail.com
text analysis approaches—subject analysis, domain analysis,
and content analysis—examining their characteristics, meth-
ods, and applications. Additionally, we will discuss their
advantages and limitations and how these techniques can be
combined to achieve a more comprehensive and in-depth un-
derstanding of textual content.
Methodology
This research has an exploratory and descriptive nature
to achieve the proposed objective, starting with a literature
review, aiming to analyze and describe the results. Thus,
bibliographic research was conducted to support the concep-
tual and theoretical-methodological discussion on subject,
content, and domain analysis, focusing on their interrelation-
ships, differences, and similarities, which are often confusing
in their concepts and methodologies.
It justifies itself by highlighting the need for more aware-
ness regarding subject analysis in Information Science, which
can lead to confusion regarding its concept, methodology, and
purpose compared to content analysis and domain analysis.
The models revealed differences in the type of strategy
used in text treatment, the approach type, and the theoretical
stance in which they fit.
CJILS/RCSIB VOL. 47, NO. 2 (2024). DOI: 10.5206/CJILS-RCSIB.V47I2.17633 159
The Definitions
Subject Analysis (SA)
Subject analysis (SA) emerged as a need to organize in-
formation in documents, making their retrieval easier. The
first bibliographic classification systems appeared in the 19th
century when the quantity of library books grew significantly.
Since then, the concern of finding efficient ways to organize
information in documents has become increasingly prominent
(Weitzel, 2002).
Subject analysis is a technique that originated in library sci-
ence and information science, aiming to assist in the organiza-
tion and retrieving information in documents. It dates back to
the development of bibliographic classification systems in the
19th century to organize library books systematically. Over
time, subject analysis has evolved to include more sophisti-
cated techniques for information organization and retrieval,
such as using keywords for information retrieval.
Cesariano and Pinto (1980) emphasize that subject analysis
is the foundational operation for information retrieval. Naves
(2000, p. 249) provides:
•a definition very close to theirs,
•describing subject analysis as a foundational operation
in subject indexing,
•encompassing the process through which the indexer
extracts the content of a document.
Lima (2020, p. 9) points out that subject analysis is an
intellectual activity, therefore subjective, starting with the
technical reading of the main parts of a document. It requires
the indexer’s linguistic, cognitive, and logical knowledge to
determine the document’s subject. Thus, as the author states,
it involves subjective procedures due to its intellectual nature.
Reading to understand and identify the text is es-
sential to later selecting valid terms to represent
the content of a document (LIMA, 2020, p. 9).
Laville and Dione (1999) also consider subject analysis a
primarily intellectual and subjective activity. In this activity,
all acquired knowledge and experiences are sharpened and
reflected in the indexer’s interpretation, aiming to objectify
subjectivity.
In Library Science and Information Science, subject anal-
ysis is the first stage of the indexing process, which involves
two steps (analysis and translation). However, in the litera-
ture, there are suggestions of three or even four stages in its
execution. Nevertheless, the UNISIST proposal (1981) with
three stages is the most cited in the literature: 1) understand-
ing the content of the document as a whole, (2) identifying
concepts representing this content, and (3) selecting concepts
for retrieval (UNISIST, 1981).
It is important to note that, in this process, the adopted
methodological parameters should always consider the con-
text in which the documents were produced and assess the
relevance of the content for a specific audience or objective.
Content Analysis (CA)
Content analysis (CA) is a technique used in Information
Science to understand and interpret qualitative data. It in-
volves the systematic analysis of the content of a set of data,
such as interviews, documents, and other sources of informa-
tion.
In Information Science, content analysis is often employed
in user studies and research aimed at understanding the needs
and behaviours of library and information system users. The
technique can be applied to different data types, including
textual, visual, and auditory. Content analysis involves iden-
tifying themes and patterns in the data and interpreting and
explaining these themes. The technique can be carried out
manually or with the assistance of specific software tools.
According to Cunha (1983), this research technique is
much older than its denomination suggests. He points out that
studies investigating mental content, personal documents, or
interview reproductions have already used similar method-
ologies. For the author, content analysis addresses questions
relevant to the analyzed object. In communication, he high-
lights (as cited in Berelson, 1971, p. 2) content analysis as
a "research technique that aims for the objective, systematic,
and quantitative description of the manifest content of com-
munication." However, it is interesting to note that when he
turns to the field of Social Sciences, more specifically Library
Science, he refers to it as Subject Analysis. In his methodol-
ogy, he categorizes procedures to initiate the analysis: the unit
of analysis, defined as "individual units on which descriptive
and explanatory statements should be made" (Cunha, 1983,
p. 249). Another procedure is "Sampling," where a sample
of what will be studied is selected, similar to fragmenting
a document and choosing a part for analysis. Additionally,
there is the coding procedure, referring to quantifying quali-
tative research data for reproduction purposes. The definition
and meaning of codes should be relevant for better research
replication.
Câmara (2013) tells us that
in the 1920s, after World War I, due to Leavell’s
studies on propaganda employed in that war, con-
tent analysis gained systematic forces of use, tak-
ing on organized forms of investigative methods.
World War II intensified the development of pro-
paganda, and therein, it gained importance, al-
lowing many disciplines, including linguistics
and mainly autobiographical literature, to show
a preference for its use. Psychoanalysis and clin-
ical psychology use it as one of the elements for
interpreting the individual’s life. (p. 159)
160 PORTELLA & DE LIMA
Bardin (1977) proposes a methodology for content analysis
that consists of three phases:
•Pre-analysis: This phase involves an exploratory ap-
proach to the material to be analyzed. The goal is
to identify the material’s characteristics, such as its
nature, origin, form, and content. It is also essential
to define the purpose of the analysis, the criteria for
selecting data, and the categories of analysis.
•Analytical description (Exploration of the material):
In this phase, the material is systematically analyzed
based on the categories defined in the pre-analysis. The
goal is to describe the material’s content objectively
and precisely, identifying the text’s main characteristics
and elements.
•Interpretative inference (Handling the obtained results
and interpretation): In this phase, the analysis becomes
more explanatory based on the inferences made in the
analytical description. The goal is to interpret the con-
tent, identifying patterns, trends, relationships, and un-
derlying meanings.
The methodology proposed by Bardin for content analysis
involves a systematic and rigorous approach, allowing for a
deeper understanding of the content of the material being
analyzed. Bardin emphasizes that the history of content anal-
ysis is marked by constant evolution, with new approaches
and techniques being developed over time to deal with the
complexity and diversity of the analyzed data. It is intriguing
how she highlights that ’Content analysis can be an analysis
of "meanings" (e.g., thematic analysis), although it can also
be an analysis of "signifiers" (lexical analysis, analysis of
procedures.).’ (Bardin, 1977, p. 34).
Interestingly, Bardin mentions that content analysis is an
analysis of signifiers because it brings us back to subject
analysis, where she later states that the descriptive treatment
would not be exclusive as the starting point solely for content
analysis.
Domain Analysis (DA)
Domain analysis (DA) is investigating and understanding
a specific thematic domain’s contents, concepts, and termi-
nology. According to various authors, the definition of do-
main analysis may vary depending on the adopted theoretical
perspective but generally involves selecting and organizing
concepts and terms related to a specific theme.
According to Hjørland & Albrechtsen (1995), domain
analysis is
a theoretical approach to Information Science
(IS) states that the best way to understand infor-
mation in information science is to study areas
of knowledge as “discourse communities, which
are parts of the division of labor society. Or-
ganization of knowledge, structure, patterns of
cooperation, language and forms of communica-
tion, information systems, and relevance criteria
are reflections of the objects of the work of these
communities and their role in society. (Hjørland
& Albrechtsen,1995, p.400).
Besides, Hjørland (2002) states that domain analysis seeks
to map and understand the characteristics and properties of
a particular domain, providing a solid foundation for the or-
ganization and access to information. Domain analysis is
a research technique that identifies and describes a specific
knowledge field’s concepts, themes, and sub-themes. In a
theoretical approach to Information Science (IS), the best way
to understand the information is to study knowledge areas as
"communities of discourse," which are parts of the division
of labour in society.
Furthermore, Hjørland and Albrechtsen (1995) propose
that domain analysis should be understood as an investiga-
tion that encompasses not only content and terminologies
but also social structures and discursive practices within a
domain. Domain analysis is not just about ’investigating and
understanding the contents, concepts, and terminology of a
specific thematic domain.’ As Hjørland (2002) and Smiraglia
(2015) point out, it is a comprehensive study encompassing
the dynamics and interactions between concepts, practices,
and users within a given context. Smiraglia (2015) expands
this view by exploring how domains are shaped by the in-
teractions between their components and users. Additional
studies, such as those by Tennis (2003) and Beghtol (2003),
also offer valuable perspectives on the methodologies and
applications of domain analysis, highlighting the importance
of considering both professional classifications and more in-
tuitive ones.
Regarding domain analysis, it is essential to consider the
article by Hjørland (2017) published in the Encyclopedia
of Knowledge Organization, where the author substantially
updates his 2002 article. In this update, he expands this
perspective, introducing new approaches that consider the
more complex dynamics and interactions within domains,
highlighting the importance of understanding the social and
cultural contexts that influence the formation and evolution of
knowledge domains. Furthermore, it incorporates emerging
methodologies that use advanced information technologies,
such as network analysis and data mining, to map and analyze
domains more comprehensively and in a detailed way.
It is a technique that originated in different areas of knowl-
edge, including Information Systems and Library Science.
According to Hjørland and Albrechtsen (1995), in Library
Science, domain analysis originates in the study of classi-
fication and cataloguing, aiming to understand the charac-
teristics of the objects and concepts that will be organized.
CJILS/RCSIB VOL. 47, NO. 2 (2024). DOI: 10.5206/CJILS-RCSIB.V47I2.17633 161
In Information Systems, domain analysis aims to understand
the study domain of an information system and identify the
specific requirements of the system. According to Pressman
(2016), domain analysis is one of the most critical activities
in the software engineering process, as it allows developers
to understand the requirements and needs of users better.
Despite emerging in different areas, domain analysis in
Information Science has the common goal of understanding
the study domain and identifying the specific requirements
of a particular system or object of study. Over time, vari-
ous methodologies and approaches have been developed to
conduct domain analysis in different areas of knowledge.
Moreover, Domain analysis is a fundamental process for
constructing knowledge organization systems, as it identifies
the most relevant terms and concepts in a given thematic
domain. For these authors, it is a dynamic and continuous
process that should be constantly updated to keep up with
changes.
The methodology proposed by Hjørland (2002) for domain
analysis in information science involves the following steps:
•Domain Identification: Define the domain scope to be
analyzed.
•Identification of Key Theories, Concepts, and Meth-
ods: Identify the fundamental theories, concepts, and
methods used in the domain area and identify relevant
information sources.
•Identify the primary information sources relevant to the
domain, including books, articles, and databases.
•Critical Analysis of Information Sources: Conduct a
critical analysis of identified information sources, con-
sidering different theoretical and methodological per-
spectives.
•Identification of Key Documents: Identify the key doc-
uments relevant to the domain, including reports, stan-
dards, and laws.
•Critical Analysis of Key Documents: Cr itically analyze
the identified key documents, considering different the-
oretical and methodological perspectives in the field.
•Identification of Key Actors: Identify the critical actors
involved in the domain, including researchers, profes-
sionals, and institutions.
•Critical Analysis of Key Actors: Conduct a critical
analysis of the identified vital actors, considering dif-
ferent theoretical and methodological perspectives in
the field.
•Identification of Gaps in the Domain: Identify gaps in
the domain that need to be addressed by new research
and studies.
•Synthesis of Results: Synthesize the domain analysis
results into a report presenting critical theories, con-
cepts, methods, relevant information sources, key doc-
uments, actors, and identified gaps in the domain.
To elucidate the characteristics and similarities among the
analyses described above, TABLE 1 presents the definitions
of subject, content, and domain analysis based on the lit-
erature, as proposed by authors who study and apply these
techniques.
The Interfaces Between Techniques of SA, CA, and DA
As mentioned, SA, CA, and DA techniques identify, inter-
pret, and understand the meaning of document content and
knowledge domains. This work aimed to explore the in-
terfaces between these three analysis approaches to elucidate
their characteristics, methods, applications, and relationships.
Subject Analysis and Content Analysis
Subject analysis and content analysis are two research tech-
niques that are closely related. Both aim to analyze and un-
derstand the content of a text, but they differ in some aspects.
Subject analysis focuses on identifying the main themes ad-
dressed in a document to assist in organizing and retrieving
information in a collection or database. Subject analysis can
be done manually by reading and identifying the addressed
themes or using specialized software.
On the other hand, content analysis is a technique aimed
at understanding the meaning of the text as a whole. It is
primarily used in qualitative research, where the goal is to
understand individuals’ perceptions and opinions regarding
a specific topic. Content analysis involves a systematic and
rigorous approach to better understanding the analyzed ma-
terial.
Despite different objectives, subject and content analysis
can be used together to comprehensively analyze a docu-
ment’s content. For example, subject analysis can identify
the main subjects addressed in a text and content analysis can
be employed to understand the meaning of these themes and
how they relate to the broader research context.
Subject analysis and content analysis are two research tech-
niques that complement each other and can be used together
to more thoroughly analyze a text’s content. Bardin (1977)
considers subject analysis one of the stages of content analy-
sis.
Subject Analysis and Domain Analysis
Subject analysis and domain analysis are related techniques
but have different objectives. While subject analysis aims to
identify the themes present in documents, domain analysis
aims to identify the specific concepts and terms of a particular
field of knowledge.
162 PORTELLA & DE LIMA
Domain analysis is also used in areas beyond Informa-
tion Science to assist in organizing information in specialized
documents and software development. For example, in a
medical library, domain analysis would be used to identify
concepts and specific terms in the medical field, such as dis-
eases, treatments, and medications. Another application of
domain analysis is understanding user and business needs for
the software’s application.
On the other hand, subject analysis would be used to rep-
resent the specific subjects in documents, regardless of the
knowledge domain covered. For instance, in a library with
books from various knowledge areas like history, literature,
and sciences, subject analysis is used to identify the subjects
covered in the books and subsequently represent them as
terms such as "history of art," "classic novels," and "marine
animals."
Hjørland (2004) emphasizes that in domain analysis, sub-
ject analysis is used to identify the main topics and concepts
present in the domain, creating a controlled vocabulary and
defining terms and concepts used in the area. To illustrate
the interfaces between the analysis techniques, a comparative
table, TABLE 2, is presented. Structured based on eight ele-
ments considered necessary for highlighting this comparison,
namely: (1) definition, (2) characteristics, (3) objectives, (4)
functions, (5) procedures, (6) approach, (7) originating area,
and (8) key authors.
As observed, we aimed to include definitions presenting
each technique’s main characteristic in the definition element.
While subject analysis appears as a technique linked to repre-
senting the content of a document, content analysis is consid-
ered a set of communication analysis techniques, and domain
analysis has a more theoretical approach with the objective
of understanding and studying an area of knowledge.
Regarding the characteristic element, it is evident that all
are considered analysis techniques, although sometimes they
are also considered by some authors as methods or even.
Regarding the objectives element, it is clear that while
subject analysis aims to condense a document’s information,
content analysis seeks to interpret the information to under-
stand the meanings of a particular theme, and domain analysis
focuses on analyzing the coherence of a knowledge domain.
Subject analysis represents retrieval; content analysis qual-
itatively and quantitatively analyzes the occurrences of spe-
cific terms within a theme. Domain analysis seeks to under-
stand a domain in a specific context.
Regarding procedures, the subject analysis relies on tech-
nical reading to understand, identify, and select valid concepts
for representation aiming at retrieval. Content analysis is car-
ried out in three stages, with the first stage, pre-analysis, hav-
ing the most detailed procedures. Domain analysis presents
itself with ten procedures suggested by Hjørland (2002).
The subject analysis is characterized as qualitative because
it is considered a subjective process, while the content analy-
sis approach, besides being qualitative, has an extreme qual-
itative bias. In domain analysis, the approach is theoretical
and methodological.
Subject analysis originated in Library Science, while
the development of content analysis occurred in linguistics,
mainly with the studies of Bardin (1977), which contributed to
popularizing the technique. Despite domain analysis having
influences from different areas, its initial studies occurred in
computer science and later in information science with the
studies of Hjørland and Albrechsten (1995).
The principal authors who supported these studies, from
the perspective of this article, were: in subject analysis (Fos-
kett (1973), Lancaster (2004), Dias Naves (2007), Fujita
(2006, 2007, 2008, 2009, 2010); Lima (2020, 2021) ABNT
NBR 12676 (1992); in content analysis (H. Lasswell (2013),
Laurence Bardin (1977); and in domain analysis ( Hjorland &
Albrechstsen (1995), Hjorland (2002, 2004), Tennis (2003),
Smiraglia (2012).
Final Considerations
Subject, domain, and content analyses are essential for
understanding and organizing information. Subject analysis
identifies the main topics of a document, domain analysis
understands the thematic area in which it is inserted, and
content analysis explores meanings and comprehends rela-
tionships within the document’s intrinsic information.
These analyses provide procedures that allow for the effi-
cient study of informational and terminological content based
on analyzing an area’s content, theme, and domain, enabling
the representation and retrieval of information. Moreover,
they assist in discovering relevant information by decoding
what is implied, proving crucial for the organization and
preservation of information.
Based on the results of this research it is expected to clarify
the concepts and methodologies of subject analysis, content
analysis, and domain analysis, as well as understand their
relationships to contribute to understanding these concepts in
information science.
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Appendix A: Interfaces between SA, CA, and DA
CJILS/RCSIB VOL. 47, NO. 2 (2024). DOI: 10.5206/CJILS-RCSIB.V47I2.17633 165
Appendix B: Definitions of subject analysis, content analysis, and domain analysis proposed by authors in the field
