A Systematic Review of Social Networks Research in Information Systems: Building a Foundation for Exciting Future Research

Social networking applications such as blogs, instant messengers, podcasts, social networking websites (e.g., Renren in China, Vkontakte in Russia, Facebook), professional networking websites (e.g., LinkedIn), Twitter, and virtual worlds (e.g., Second Life) have become increasingly popular in the last few years. Because these applications have substantial implications for users, organizations, and society, social networks (SNs) have gained attention from information systems (IS) researchers and grown steadily as a research area since 2004. However, to organize the accumulated research and encourage researchers to examine new and pressing issues in SNs, available knowledge needs to be synthesized and research gaps need to be addressed (Bandara et al., 2011). Therefore, we systematically reviewed publications about SNs published in major IS journals between January 2004 and August 2013 and, in this paper, overview the state of IS research regarding SNs. We show the evolution of the existing IS research on SNs to build a common nomenclature and taxonomy for this area of research, to identify theories used, and to provide a useful roadmap for future research in this area

Research Models in Information Systems

The use of research models in driving scholarly investigation is of great importance in any field, including information systems (IS). As such, a taxonomy of IS research models should be of substantial value to the discipline. Such a taxonomy is developed in this article based on the IS research literature. Eleven model types are examined in detail in order to investigate how they are used by researchers, in articles published in seven leading IS journals during a recent six year period. Interesting results emerge in the use of models overall, as well as trends over time and relationships with specific methodologies and IS journals. Multi-tier influence diagram is the most used research model in IS research, while the no model, listing of variables, mathematical model, and simple influence diagram also find significant usage among the IS research community. Patterns of model use were also identified based on top journals and prevalent research methodologies

A Review of the Literature on the Empathy Construct Using Cluster Analysis

Empathy plays a central role in human behavior and is a key aspect of social functioning. The extensive research on the empathy construct in fields such as psychology, social work, and education has revealed many positive aspects of empathy. Through the use of cluster analysis, this research takes a new approach to reviewing the literature on empathy and objectively identifies groups of empathy research. Next, this study relates the information systems (IS) discipline’s focus on empathy research through the projection of IS empathy paragraphs into those clusters, and identifies areas of empathy research that are currently being largely overlooked by the IS field. The use of cluster analysis and projection for conducting a literature review provides researchers with a more objective approach for reviewing relevant literature

Research Models in Information Systems

The use of research models in driving scholarly investigation is of great importance in any field, including information systems (IS). As such, a taxonomy of IS research models should be of substantial value to the discipline. Such a taxonomy is developed in this article based on the IS research literature. Eleven model types are examined in detail in order to investigate how they are used by researchers, in articles published in seven leading IS journals during a recent six year period. Interesting results emerge in the use of models overall, as well as trends over time and relationships with specific methodologies and IS journals. Multi-tier influence diagram is the most used research model in IS research, while the no model, listing of variables, mathematical model, and simple influence diagram also find significant usage among the IS research community. Patterns of model use were also identified based on top journals and prevalent research methodologies

A citation analysis of the ACSC 2006 - 2008 proceedings, with reference to the CORE conference and journal rankings

This paper compares the CORE rankings of computing conferences and journals to the frequency of citation of those journals and conferences in the Australasian Computer Science Conference (ACSC) 2006, 2007 and 2008 proceedings. The assumption underlying this study is that there should be a positive relationship between citation rates and the CORE rankings. Our analysis shows that the CORE rankings broadly reflect the ACSC citations, but with some anomalies. While these anomalies might be minor in the larger scheme of things, anomalies need to be addressed, as the careers of individual academics may depend upon it. Rankings are probably here to stay, and this paper ends with some suggestions on how the rankings process should now evolve, so that it becomes more transparent. Copyright © 2009, Australian Computer Society, Inc

Journal Self-Citation IV: Citations Analysis of IS Journals – Separating Facts from Fiction

This article is inspired by a recent posting on the AISWorld listserv eliciting thoughts on the practice of self-citations by journals in the IS field. While emotions ran high in the ensuing online discussion, we try to provide an objective and informed analysis of the actual citation patterns of both top tier journals and non-top tier journals. Results show that the practice of self-citation is fairly common among both types of journals. Additional analyses showed that the preference for top-tier citations was more prevalent in top-tier journals than in non-top-tier journals. Supported by the data, we provide several arguments for these practices

Journal Self-Citation IV: Citations Analysis of IS Journals – Separating Facts from Fiction

This article is inspired by a recent posting on the AISWorld listserv eliciting thoughts on the practice of self-citations by journals in the IS field. While emotions ran high in the ensuing online discussion, we try to provide an objective and informed analysis of the actual citation patterns of both top tier journals and non-top tier journals. Results show that the practice of self-citation is fairly common among both types of journals. Additional analyses showed that the preference for top-tier citations was more prevalent in top-tier journals than in non-top-tier journals. Supported by the data, we provide several arguments for these practices

A Scientometric Investigation into the Validity of IS Journal Quality Measures

In this study we investigated the measurement validity of the findings in the IS journal quality stream over the past ten years. Our evaluation applied a series of validation tests to the metrics presented in these studies using data from multiple sources. The results of our tests for content, convergent, and discriminant validity, as well as those for parallel-form, test-retest, and item-to-total reliability, were highly supportive. From these findings, we conclude that recent studies in the IS journal quality stream are credible. As such, these IS journal quality measures provide appropriate indicators of relative journal quality. This conclusion is important for both academic administrators and scientometric researchers, the latter of whom depend on journal quality measures in the evaluation of published IS research

Using Social Network Analysis to Analyze Relationships Among IS Journals

Social network analysis (SNA) offers a richer and more objective way of examining individual journal influence and relationships among journals than studies based on individual perceptions, since it avoids personal biases. This article demonstrates how SNA can be used to study the nature of the IS discipline, by presenting results from an exploratory SNA of 125 previously ranked journals from IS and allied disciplines. While many of the most prominent journals in the network are still associated with IS’s foundational disciplines, we identify several IS journals that play important roles in disseminating information throughout different subcomponents of the network. We also identify related groups of journals based not only on patterns of information flow, but also on similarity in citation patterns. This enables us to identify the core set of journals that is important for “pure IS” research, as well as other subsets of journals that are important for specialty areas of interest. Overall, results indicate that the IS discipline is still somewhat fragmented and is still a net receiver, as opposed to a net provider, of information from allied disciplines. Like other forms of analysis, SNA is not entirely free from biases. However, these biases can be systematically researched in order to develop an improved, consistent tool with which to examine the IS field via citations among member journals. Thus, while many challenges remain in applying SNA techniques to the study of IS journals, the opportunity to track trends in the discipline over time, with a larger basket of journals, suggests a number of valuable future applications of SNA for understanding the IS publication system