A Scientometric and Social Network Analysis of the Literature on the Graph Model for Conflict Resolution

2023 | Group Decision and Negotiation | Citations: 0

Authors: de Andrade, Ricardo Lopes; Silva, Maísa Mendonça; Rêgo, Leandro Chaves

Abstract: Over the 35 years of its existence, the Graph Model for Conflict Resolution (GMC ... Expand

Abstract: Over the 35 years of its existence, the Graph Model for Conflict Resolution (GMCR) has shown to be a valuable tool for conflict analysis. Many developments and applications of the GMCR have been made in this period. This paper aims to provide valuable information for understanding the global panorama of research in the GMCR by means of a scientometric and social network analysis (SNA). To do so, we utilize the software VOSviewer for examining papers from 1987 until 2021 published in journals which are listed in the Web of Science (WoS) database. The results reveal insights about key countries, organizations, authors and journals in the area providing valuable information for both practitioners and researchers in terms of past developments and trends for future research. Collapse

Topics: database system

Methods: co-authorship network bibliometric analysis social network analysis longitudinal data analysis theoretical contribution

An ensemble model for link prediction based on graph embedding

2022 | Decision Support Systems | Citations: 0

Authors: Chen, Yen-Liang; Hsiao, Chen-Hsin; Wu, Chia-Chi

Abstract: A network is a form of data representation and is widely used in many fields. Fo ... Expand

Abstract: A network is a form of data representation and is widely used in many fields. For example, in social networks, we regard nodes as individuals or groups, and the edges between nodes are called links, that is, the interaction between people. By analyzing the interaction of nodes, we can learn more about network relationships. The core idea of link prediction is to predict whether there is a new relationship between a pair of nodes or to discover hidden links in the network. Link prediction has been applied to many fields such as social networking, ecommerce, bioinformatics, and so on. In addition, many studies have used graph embedding for link prediction, which effectively preserves the network structure and converts node information into a low-dimensional vector space. In this research, we used three graph embedding approaches: matrix decomposition based methods, random walk based methods, and deep learning based methods. Since each method has its own advantages and disadvantages, we propose an ensemble model to combine these graph embeddings into a new representation of each node. Then, we designed a two-stage link prediction model based on a multi-classifier ensemble and took the new node representation as its input. Performance evaluation was conducted on multiple data sets. Exper­ imental results show that the integration of multiple embedding methods and multiple classifiers can signifi­ cantly improve the performance of link prediction. Collapse

Topics: electronic mail wiki social network Wikipedia

Methods: logistic regression machine learning deep learning support vector machine ensemble learning

Bibliometric Analysis of Sustainability Information Systems Research

2022 | Americas Conference on Information Systems | Citations: 0

Authors: El-Rayes, Nesreen; Abraham, Thomas; Dao, Viet

Abstract: As IS literature on Sustainability has evolved significantly, reviews of the li ... Expand

Abstract: As IS literature on Sustainability has evolved significantly, reviews of the literature tend to focus more on Green IT, and Green IS research and utilize a smaller body of literature. To help enhance understanding of the evolution of IS and Sustainability literature, this research examines an extensive body of knowledge. We used a comprehensive list of keywords to retrieve research related to Green IT, Green IS, and Sustainability IS. We searched for work beyond a limited list of outlets using the SCOPUS database with an extended timeframe. We then conducted a bibliometric analysis using text-mining tools to provide a clearer view of the field and its themes, thus it helps address what, where, and when questions about the nature of research in SIS literature, providing insights on what topics have been studied, where the research originated from, how the body of research has evolved over the years, and suggested future research. Collapse

Topics: green IS database system blockchain internet of things mobile system

Methods: natural language processing VOSviewer bibliometric analysis network analysis cluster analysis

Authorship, Collaboration, and Influence of Women IS Scholars: Using Social Network Analysis

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Zhou, Shimi; Loiacono, Eleanor; Nerur, Sridhar; Randolph, Adriane; Lingo, Elizabeth; Iyer, Lakshmi; Carter, Michelle

Abstract: Research productivity is a critical component of any academic's career progress ... Expand

Abstract: Research productivity is a critical component of any academic's career progression. Thus, when trying to understand the underrepresentation issues surrounding women in the information systems (IS) field, research networks are a reasonable starting point. This study aims to understand the trends and patterns of IS women academics' citation networks that impact their productivity and promotability. Social network analysis (SNA) techniques that analyze bibliographic data extracted from the IS senior scholar's basket of eight journals between 1990 and 2021 are employed. In addition to this comprehensive article search, author attributes such as gender, affiliation, Ph.D. granting institution, and ethnicity, will be collected. Using these network member attributes, we will analyze the extent of homophily and its influence on forming co-author ties in IS. SNA will help us understand the complexity and potential impacts of authorship and collaboration networks in a diverse and inclusive IS community. Collapse

Topics: productivity database system Python website

Methods: co-citation analysis self reported survey social network analysis co-authorship network longitudinal data analysis

Forty years of the International Journal of Information Management: A bibliometric analysis

2021 | International Journal of Information Management | Citations: 3

Authors: Donthu, Naveen; Kumar, Satish; Pandey, Nitesh; Gupta, Prashant

Abstract: In 2019, the International Journal of Information Management (IJIM) celebrated i ... Expand

Abstract: In 2019, the International Journal of Information Management (IJIM) celebrated its 40th year of publication. This study commemorates this event by presenting a retrospect of the journal. Using a range of bibliometric tools, we find that the journal has grown impressively in terms of publication and citation. The contributions come from all over the world, but the majority are from Europe and the United States. The journal has mostly published empirical articles, with its authors dominantly using quantitative methodology. Further, the culture of collab­ oration has increased among authors over the years. The journal publishes on a number of including managing information systems, information technologies and their application in business, technology acceptance among consumers, using information systems for decision making, social perspectives on knowledge management, and information research from the social science perspective. Regression analysis reveals that article attributes such as article order, methodology, presence of authors from Europe, number of references, number of keywords, and abstract length have a significant association with the citations. Finally, we find that conceptual and review articles have a positive association with citations. Collapse

Topics: information management strategic management search engine IS management decision support system

Methods: descriptive statistic bibliometric analysis co-citation analysis literature sample theory development

Mapping World Scientific Collaboration on the Research of COVID-19: Authors, Journals, Institutions, and Countries

2021 | HICSS | Citations: 0

Authors: Zhao, Rongying; Liu, Zhuozhu; Zhang, Xiaoxi; Wang, Junling; Zhang, Zhaoyang

Abstract: The COVID-19 (2019 novel Coronavirus) is the most widespread pandemic infectious ... Expand

Abstract: The COVID-19 (2019 novel Coronavirus) is the most widespread pandemic infectious disease encountered in human history. Its economic losses and the number of countries involved rank first in the history of human viruses. After the outbreak, researchers in the field of medicine quickly carried out scientific research on the virus. Through a visual analysis of relevant scientific research papers from January 1st to April 1st, 2020, we can grasp the worldwide scientific research cooperation situation of 2019-nCoV research and reflect the international collaboration in combating the pandemic. To this end, 415 papers indexed in Thomson Reuters’s Web of Science were studied to provide a visualized description of scientific collaborations across the world by multiple levels, including author level, journal level, institution level and country level. Collapse

Topics: pandemic database system covid 19

Methods: literature sample VOSviewer co-citation analysis bibliometric analysis descriptive statistic

Analyzing Co-authorship Network for Homophily – Evidence from IS senior Scholar’s Basket of Eight Journals for Business Analytics Research

2020 | Americas Conference on Information Systems | Citations: 0

Authors: Dwivedi, Rahul; Nerur, Sridhar

Abstract: The aim of this study is to create a co-authorship network for business analyti ... Expand

Abstract: The aim of this study is to create a co-authorship network for business analytics research published in the IS senior scholar's basket of eight journals over 20 years (1997 -2016) and to test for homophily based on certain author characteristics. The resulting network is analyzed using Exponential Random Graph Modeling (ERGM). Our results show that there is evidence of homophily. Specifically, authors' continental affiliations, departmental affiliations, and affiliations based on Ph.D. granting institutions and universities are significant predictors of co-authorship links. Authors' genders and post-Ph.D. experience were insignificant. Results suggest that there is no evidence of homophily in the collaborations between men and women scholars publishing Business Analytics articles in leading IS journals. Also, the insignificance of experience as a predictor of scholarly collaboration suggests that recent postdoctoral researchers collaborate with colleagues who have had a longer tenure in their fields. Collapse

Topics: analytical information system social network database system business intelligence programming language

Methods: co-authorship network Poisson regression descriptive statistic machine learning social network analysis

Assessing the long-term fragmentation of information systems research with a longitudinal multi-network analysis

2019 | European Journal of Information Systems | Citations: 0

Authors: Khan, Gohar Feroz; Trier, Matthias

Abstract: Over the decades, the evolving information systems (IS) research community and i ... Expand

Abstract: Over the decades, the evolving information systems (IS) research community and its academic output has greatly expanded. This paper offers an integrated analysis of multiple dimensions of network interconnectedness of the growing IS discipline. In line with the social and intellectual dimensions of the underlying theory of science, we synthesise multiple network views on authors, institutions, journal outlets, citations, and themes into a multi-dimensional knowledge network infrastructure analysis of collaborative networks of IS researchers and their academic output. We further introduce two fragmentation types to better address the dynamics of the IS discourse discussed in previous research. Based on a corpus of all 3587 AIS basket of 8 journal articles over 20 years, we use the analytical framework to study whether the fast growth of the IS discipline resulted in a reduced coherence of the overall academic collaboration and the research themes. The analysis reveals that the sampled IS researcher community developed a large core component with influential bridging people who mitigate fragmentation and centralisation. This IS community structure constitutes a valuable asset to cope with fragmentation tendencies in the intellectual dimension (research topics) resulting from many short-term topic bursts and from centralisation of conceptual terms. Collapse

Topics: IS discipline social network IT skill network infrastructure technology adoption

Methods: cluster analysis network analysis co-authorship network co-citation analysis longitudinal research

Theories: social network theory

The Personal in the Policy Cascade

2019 | Journal of the Association for Information Systems | Citations: 1

Authors: Winter, Susan; Saunders, Carol

Abstract: Policy change can cascade down from law and regulation, but Giddens’ structurati ... Expand

Abstract: Policy change can cascade down from law and regulation, but Giddens’ structuration theory argues that it can also flow upward from everyday action. We all have the power to take immediate action in our professional lives to create the policies we want. We use the example of gender equality to show the daily choices that you as an IS academic can make that strengthen or change existing policies. You can enhance the voices of members of undervalued groups, reduce inequities in access to resources and positions of power, and create and enforce rules, regulations, and codes that encourage more equitable outcomes. Policy influences action, but action equally influences policy. Your everyday actions either reinforce existing policies and structures or undermine and change them. We should make these choices mindfully, with an understanding of the power we are wielding, the values we are enacting, and the society we are creating. Collapse

Topics: big data

Methods: co-authorship network

Theories: structuration theory

Exploratory key nodes in the inventor-author knowledge diffusion network

2018 | HICSS | Citations: 0

Authors: Zhang, Guijie; Wei, Fangfang; Shao, Zhen

Abstract: This paper aims to mine the key nodes in the process of knowledge flow from lite ... Expand

Abstract: This paper aims to mine the key nodes in the process of knowledge flow from literatures of science and technology journals to technology patents on the community level. Based on the citation of technological patents to literatures of scientific journals and the cooperation among the researchers, this paper builds the knowledge flow network from the angle of spatial dimension. Then employing the extensity centralityNewman and the commonly used degree indexes, this paper excavates and analyses the nodes which occupy important positions among communities in the knowledge flow network. After that, this paper puts forward suggestions on how to make full use of the key nodes’ role of bridge to promote knowledge flow from literatures of science and technology journals to technology patents. Collapse

Topics: Java website

Methods: descriptive statistic theoretical contribution co-authorship network case study