Author Co-citation Analysis Research Articles

Can citation analysis of Web publications better detect research fronts?

AbstractWe present evidence that in some research fields, research published in journals and reported on the Web may collectively represent different evolutionary stages of the field, with journals lagging a few years behind the Web on average, and that a “two‐tier” scholarly communication system may therefore be evolving. We conclude that in such fields, (a) for detecting current research fronts, author co‐citation analyses (ACA) using articles published on the Web as a data source can outperform traditional ACAs using articles published in journals as data, and that (b) as a result, it is important to use multiple data sources in citation analysis studies of scholarly communication for a complete picture of communication patterns. Our evidence stems from comparing the respective intellectual structures of the XML research field, a subfield of computer science, as revealed from three sets of ACA covering two time periods: (a) from the field's beginnings in 1996 to 2001, and (b) from 2001 to 2006. For the first time period, we analyze research articles both from journals as indexed by the Science Citation Index (SCI) and from the Web as indexed by CiteSeer. We follow up by an ACA of SCI data for the second time period. We find that most trends in the evolution of this field from the first to the second time period that we find when comparing ACA results from the SCI between the two time periods already were apparent in the ACA results from CiteSeer during the first time period.

Evolution of the Intellectual Structure of Family Business Literature: A Bibliometric Study of FBR

This article aims at identifying the characteristics of the family business as a differentiated field within management. For that aim, we use author co-citation analysis (ACA) to identify different research trends within the field, studying all the papers published in the Family Business Review from its foundation in 1988 through to the December 2005 issue. Results show that despite the literature being fragmented and showing a lack of consensus, we are facing, in Kuhn's words, a development of the research frontier by enlarging the number of approaches used for understanding the family business.

Domain analysis for the construction of a conceptual structure : a case study

This work describes the construction of a conceptual structure, as a result of the domain analysis of the current research on Benign Prostatic Hyperplasia (BPH), through different techniques based on the citations and semantic analysis. A sample which covers all published articles about the disease in mainstream journals was chosen. A total of 1,968 articles from 2000 through 2004 were retrieved from Science Citation Index. Author Co-citation Analysis (ACA) techniques and semantic analysis were used and the results were represented by different informatic programs. A macrostructure of the domain of the current research on BPH was identified through bibliometric techniques. The text mining techniques allowed validation of the identified macrostructure and the obtainment of the most frequent words in the text. The semantic analysis of the most cited reviews on BPH during the studied period allowed the definition of the categories to be used in the structure. Finally, a conceptual structure to be used as controlled (structured) language in the information retrieval, inside of a specialized information system on the approach of the disease is shown.

Structure of personality psychology based on cocitation analysis of prominent authors

Traditional Author Cocitation Analysis was applied in order to map the personality psychology as a research field. A group of 25 authors were selected from the Haggbloom (1999, 2002) lists of the most cited and prominent psychologists, judged to be the main contributors to the field. All of their cocitations identified in the three year volumes of SSCI were downloaded to be analyzed by cluster analysis and MDS. The analysis resulted in four clusters comprising (1) theorists of individual differences amalgamated with authors of biological orientation with R. Cattell positioned centrally, (2) behaviorists joined by socio-cognitive theorists led by M.E.P. Seligman and A. Bandura, and (3) the group of psychoanalytic (dynamic) theorists with A. Adler in the middle. In fourth cluster G. Allport, H. Murray, K. Lewin, W. Mischel, and D. Buss were found mixed together to make a rather heterogeneous group. In two-axes representation one of the dimensions was understood as reflecting methodological and the other one content-specific differences among the authors, although this interpretation is not univocal. The same procedure was repeated on citations given to the same authors in SocioFakt - the Serbian Citation Index for Social Sciences, revealing a reduced picture of the domain. At this portrait, some important authors are missing as a result of their low citation rate, suggesting that in the Serbian personality psychology entire research fields don?t exist. .

Author Cocitation Analysis is to intellectual structure as Web Colink Analysis is to …?

AbstractAuthor Cocitation Analysis (ACA) and Web Colink Analysis (WCA) are examined as sister techniques in the related fields of bibliometrics and webometrics. Comparisons are made between the two techniques based on their data retrieval, mapping, and interpretation procedures, using mathematics as the subject in focus. An ACA is carried out and interpreted for a group of participants (authors) involved in an Isaac Newton Institute (2000) workshop—Singularity Theory and Its Applications to Wave Propagation Theory and Dynamical Systems—and compared/contrasted with a WCA for a list of international mathematics research institute home pages on the Web. Although the practice of ACA may be used to inform a WCA, the two techniques do not share many elements in common. The most important departure between ACA and WCA exists at the interpretive stage when ACA maps become meaningful in light of citation theory, and WCA maps require interpretation based on hyperlink theory. Much of the research concerning link theory and motivations for linking is still new; therefore further studies based on colinking are needed, mainly map‐based studies, to understand what makes a Web colink structure meaningful.

Towards all-author co-citation analysis

The present study examines one of the fundamental aspects of author co-citation analysis (ACA): the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting: on the one hand, the traditional type that only counts the first one among a cited work’s authors, and on the other hand, a simplified approach to all-author co-citation counting that takes into account the first five authors of a cited work. Results indicate that the picture produced through this simplified all-author co-citation counting contains author groups that are more coherent, and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed. Variations of counting more than first authors are compared.

Theoretical studies of the historical development of the accounting discipline: A review and evidence

Many existing studies of the development of accounting thought have either been atheoretical or have adopted Kuhn's model of scientific growth. The limitations of this 35-year-old model are discussed. Four different general neo-Kuhnian models of scholarly knowledge development are reviewed and compared with reference to an analytical matrix. The models are found to be mutually consistent, with each focusing on a different aspect of development. A composite model is proposed. Based on a hand-crafted database, author co-citation analysis is used to map empirically the entire literature structure of the accounting discipline during two consecutive time periods, 1972–81 and 1982–90. The changing structure of the accounting literature is interpreted using the proposed composite model of scholarly knowledge development.

A connectionist and multivariate approach to science maps: the SOM, clustering and MDS applied to library and information science research

The visualization of scientific field structures is a classic of scientometric studies. This paper presents a domain analysis of the library and information science discipline based on author co-citation analysis (ACA) and journal cocitation analysis (JCA). The techniques used for map construction are the self-organizing map (SOM) neural algorithm, Ward's clustering method and multidimensional scaling (MDS). The results of this study are compared with similar research developed by Howard White and Katherine McCain [1]. The methodologies used allow us to confirm that the subject domains identified in this paper are, as well, present in our study for the corresponding period. The appearance of studies pertaining to library science reveals the relationship of this realm with information science. Especially significant is the presence of the management on the journal maps. From a methodological standpoint, meanwhile, we would agree with those authors who consider MDS, the SOM and clustering as complementary methods that provide representations of the same reality from different analytical points of view. Even so, the MDS representation is the one offering greater possibilities for the structural representation of the clusters in a set of variables.

Exploring co‐citation chains

AbstractThe game “Six Degrees of Kevin Bacon” is played by naming an actor and then, by thinking of other actors in movies such that a chain of connections can be made, linking the named actor with Kevin Bacon. The number of different movies that are used to link the actor to Bacon indicate the degree with which the two are linked. For example, using John Travolta as the named actor, he appeared in the movie Look Who' s Talking with Kirstie Alley, who was in She' s Having a Baby with Kevin Bacon. So, John Travolta has a Bacon number or degree of two, as connected via Kirstie Alley. (For a more thorough discussion, see (http://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon). The example is taken from (http://www.geocities.com/theeac/bacon.html)). Based on the above, perhaps another title for this paper could be the “Six Degrees of Sir Francis Bacon,” as it indicates the framework for this paper by relating it to the above technique but placing it in an academic domain through the use of a scholarly bibliographic database. Additionally, the bibliometric technique of author co‐citation analysis (ACA) will be used to help by automating the process of finding the connections.

Mapping the field of human‐computer interaction (HCI)

AbstractHuman‐Computer Interaction (HCI) is a multidisciplinary field which combines the theories and practices from a number of fields including computer science, cognitive and behavioral psychology, anthropology, sociology, ergonomics, industrial design, and more. We use author cocitation analysis to explore the interrelationships between the specialties or sub‐communities within the field of HCI.

The use of bibliometric and knowledge elicitation techniques to map a knowledge domain: Software Engineering in the 1990s

Parallel mappings of the intellectual and cognitive structure of Software Engineering (SE) were conducted using Author Cocitation Analysis (ACA), PFNet Analysis, and card sorting, a Knowledge Elicitation (KE) method. Cocitation counts for 60 prominent SE authors over the period 1990 - 1997 were gathered from SCISEARCH. Forty-six software engineers provided similar data by sorting authors’ names into labeled piles. At the 8 cluster level, ACA and KE identified similar author clusters representing key areas of SE research and application, though the KE labels suggested some differences between the way that the authors’ works were used and how they were perceived by respondents. In both maps, the clusters were arranged along a horizontal axis moving from “micro” to “macro” level R&D activities (correlation of X axis coordinates = 0.73). The vertical axis of the two maps differed (correlation of Y axis coordinates = -0.08). The Y axis of the ACA map pointed to a continuum of high to low formal content in published work, whereas the Y axis of the KE map was anchored at the bottom by “generalist” authors and at the top by authors identified with a single, highly specific and consistent specialty. The PFNet of the raw ACA counts identified Boehm, Basili, and Booch as central figures in subregions of the network with Boehm being connected directly or through a single intervening author with just over 50% of the author set. The ACA and KE combination provides a richer picture of the knowledge domain and provide useful cross-validation.

저자 동시인용분석에 의한 국내외 기록관리학 분야의 지적구조 비교에 관한 연구

This study investigated the intellectual structure of records management and archives field in Korea and America using author cocitation analysis. Major journals in the field from 2000 to 2004 are used to select frequent cited authors. Cocited authors are analyzed in details by means of multi-variate statistical techniques such as multidimensional scaling. To the analysis of this intellectual structure, main research topics in Korea were laws and policies related to records management and archives whereas information technology based electronic records management in America.

Current paradigms in the international management field: An author co-citation analysis

Although many papers have aimed at describing the evolution of the International Management (IM) field, most of them have applied a subjective approach. Instead of trying to establish the most current research lines or interests, this study investigates the intellectual structure that serves as a basis for the IM research. To achieve this aim, we try to identify the main research trends used in the most relevant IM journals. By means of the co-citation analysis, we analyze the articles published in five top journals from 1997 to 2000, identifying the main trends and analyzing their dissemination within those journals.

Similarity measures, author cocitation analysis, and information theory

AbstractThe use of Pearson's correlation coefficient in Author Cocitation Analysis was compared with Salton's cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. However, one has the option of applying a logarithmic transformation in correlation analysis. Information calculus is based on both the logarithmic transformation and provides a non‐parametric statistics. Using this methodology, one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used on the data set, which was made the subject of this discussion.

Going beyond counting first authors in author co‐citation analysis

AbstractThe present study examines one of the fundamental aspects of author co‐citation analysis (ACA) ‐ the way co‐citation counts are defined. Co‐citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co‐citation counting ‐ the traditional type that only counts the first one among a cited work's authors on the one hand and a non‐traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non‐traditional author co‐citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first‐author co‐citation counting when the same number of top‐ranked authors is selected and analyzed. Reasons for these effects are discussed.

Bibliometric Analysis of the Science of Human Factors

Domain visualization attempts to present the interrelationships between research areas by spatially representing the fields or sub fields of science. The science of human factors has grown over the past decade. In addition, sub specialties within the field have developed making it even more complex to understand. As a future human factors practitioner, understanding a multidisciplinary field such as this necessitates a domain analysis because of its evolutionary and complex nature. This paper reports the preliminary results of this analysis using author co-citation analysis (ACA) and three domain visualization tools, cluster analysis, multidimensional scaling, and Pathfinder Networks. Sixty authors were mapped selected from core ergonomics, human factors (HF) and human computer interaction (HCI) journals. Preliminary results suggest that ergonomics is treated as a separate entity, while HF and HCI are more intertwined with some key researchers forming the core of the research community. Future research directions are discussed.

Pearson's r and author cocitation analysis: A commentary on the controversy

Pearson's <i>r</i> and author cocitation analysis: A commentary on the controversy

Author cocitation analysis and Pearson's r

Author cocitation analysis and Pearson's <i>r</i>

Author cocitation analysis and Pearson's r

AbstractIn their article “Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient,” Ahlgren, Jarneving, and Rousseau fault traditional author cocitation analysis (ACA) for using Pearson's r as a measure of similarity between authors because it fails two tests of stability of measurement. The instabilities arise when rs are recalculated after a first coherent group of authors has been augmented by a second coherent group with whom the first has little or no cocitation. However, AJ&amp;R neither cluster nor map their data to demonstrate how fluctuations in rs will mislead the analyst, and the problem they pose is remote from both theory and practice in traditional ACA. By entering their own rs into multidimensional scaling and clustering routines, I show that, despite r's fluctuations, clusters based on it are much the same for the combined groups as for the separate groups. The combined groups when mapped appear as polarized clumps of points in two‐dimensional space, confirming that differences between the groups have become much more important than differences within the groups—an accurate portrayal of what has happened to the data. Moreover, r produces clusters and maps very like those based on other coefficients that AJ&amp;R mention as possible replacements, such as a cosine similarity measure or a chi square dissimilarity measure. Thus, r performs well enough for the purposes of ACA. Accordingly, I argue that qualitative information revealing why authors are cocited is more important than the cautions proposed in the AJ&amp;R critique. I include notes on topics such as handling the diagonal in author cocitation matrices, lognormalizing data, and testing r for significance.

Pathfinder networks and author cocitation analysis: A remapping of paradigmatic information scientists

AbstractIn their 1998 article “Visualizing a discipline: An author cocitation analysis of information science, 1972–1995,” White and McCain used multidimensional scaling, hierarchical clustering, and factor analysis to display the specialty groupings of 120 highly‐cited (“paradigmatic”) information scientists. These statistical techniques are traditional in author cocitation analysis (ACA). It is shown here that a newer technique, Pathfinder Networks (PFNETs), has considerable advantages for ACA. In PFNETs, nodes represent authors, and explicit links represent weighted paths between nodes, the weights in this case being cocitation counts. The links can be drawn to exclude all but the single highest counts for author pairs, which reduces a network of authors to only the most salient relationships. When these are mapped, dominant authors can be defined as those with relatively many links to other authors (i.e., high degree centrality). Links between authors and dominant authors define specialties, and links between dominant authors connect specialties into a discipline. Maps are made with one rather than several computer routines and in one rather than many computer passes. Also, PFNETs can, and should, be generated from matrices of raw counts rather than Pearson correlations, which removes a computational step associated with traditional ACA. White and McCain's raw data from 1998 are remapped as a PFNET. It is shown that the specialty groupings correspond closely to those seen in the factor analysis of the 1998 article. Because PFNETs are fast to compute, they are used in AuthorLink, a new Web‐based system that creates live interfaces for cocited author retrieval on the fly.