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"Social network analysis"
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The effect of the board on corporate social responsibility: bibliometric and social network analysis
This is the first study that presents a full picture of the field by using a combination of two methodologies, bibliometric and social network analysis (SNA). Thus, this work maps the knowledge of previous research and suggest new avenues for future research for the relationship between board characteristics and corporate social responsibility (CSR) and CSR disclosure (CSRD). We analysed 242 articles published on Web of Science database (WoS) journals for the period 1992-2019. The results show that board characteristics have a significant impact on CSR literature in terms of citations and high-quality journals. Moreover, the trend of the papers published in the field is increasing in the last five years. Our work clusters the literature according to keywords and draws the primary authors' networks. This study also draws potential future avenues for research in the field in terms of research gaps (governance mechanisms, variables, countries, etc.). Furthermore, our results suggest some potential areas of interest for future political reforms of board of directors' guidelines.
Journal Article
Biographical Reconstructive Network Analysis (BRNA): A Life Historical Approach in Social Network Analysis of Older Migrants in Australia
Während qualitative Ansätze in der sozialen Netzwerkanalyse florieren, sind Forschungsprozesse und insbesondere die Datenanalyse zumeist von einem strukturalen netzwerkanalytischen Paradigma geprägt. Zudem existieren unzureichend qualitativ-interpretative Ansätze zur Untersuchung sozialer Netzwerkdaten. Um diese Forschungslücke zu schließen, entwerfen und explizieren wir ein qualitatives Analyseverfahren, das auf dem Cultural Turn der sozialen Netzwerkanalyse aufbaut und sowohl subjektive Deutungsmuster als auch historisch/prozessuale Konfigurationen erfassen soll. Wir formulieren eine biografische netzwerkanalytische Perspektive, in der wir die Entwicklung eines sozialen Netzwerkes in der Lebensgeschichte analysieren. Am Beispiel einer Fallstudie aus einem Forschungsprojekt zu transnationalen sozialen Unterstützungsnetzwerken älterer Migrant*innen in Perth explizieren wir das Verfahren der biografisch rekonstruktiven Netzwerkanalyse (BRNA). BRNA ist ein kooperativ entwickeltes analytisches Verfahren der Erhebung und der Auswertung sozialer Netzwerkdaten. Bei der BRNA-Datenerhebung werden das narrativ-biografische Interview und ego-zentrische Netzwerkkarten trianguliert. Bei der Datenanalyse folgen wir biografisch-rekonstruktiven Forschungsprinzipien und Verfahren, um die Dynamiken sozialer Netzwerke in der Lebensgeschichte zu rekonstruieren und nachzuvollziehen.
Journal Article
Epinets
Epinets presents a new way to think about social networks, which focuses on the knowledge that underlies our social interactions. Guiding readers through the web of beliefs that networked individuals have about each other and probing into what others think, this book illuminates the deeper character and influence of relationships among social network participants.
Drawing on artificial intelligence, the philosophy of language, and epistemic game theory, Moldoveanu and Baum formulate a lexicon and array of conceptual tools that enable readers to explain, predict, and shape the fabric and behavior of social networks. With an innovative and strategically-minded look at the assumptions that enable and clog our networks, this book lays the groundwork for a leap forward in our understanding of human relations.
eBook
Understanding criminal networks : a research guide
\"Understanding Criminal Networks is a short methodological primer for those interested in studying illicit, deviant, covert, or criminal networks using social network analysis (SNA). Accessibly written by Gisela Bichler, a leading expert in SNA for dark networks, the book is chock-full of graphics, checklists, software tips, step-by-step guidance, and straightforward advice. Covering all the essentials, each chapter highlights three themes: the theoretical basis of networked criminology; methodological issues and useful analytic tools; and producing professional analysis. Unlike any other book on the market, the book combines conceptual and empirical work with advice on designing networking studies, collecting data, and analysis. Relevant, practical, theoretical, and methodologically innovative, Understanding Criminal Networks promises to jumpstart readers' understanding of how to cross over from conventional investigations of crime to the study of criminal networks\"-- Provided by publisher.
Book
Mapping theme trends and knowledge structures for human neural stem cells: a quantitative and co-word biclustering analysis for the 2013-2018 period
Neural stem cells, which are capable of multi-potential differentiation and self-renewal, have recently been shown to have clinical potential for repairing central nervous system tissue damage. However, the theme trends and knowledge structures for human neural stem cells have not yet been studied bibliometrically. In this study, we retrieved 2742 articles from the PubMed database from 2013 to 2018 using \"Neural Stem Cells\" as the retrieval word. Co-word analysis was conducted to statistically quantify the characteristics and popular themes of human neural stem cell-related studies. Bibliographic data matrices were generated with the Bibliographic Item Co-Occurrence Matrix Builder. We identified 78 high-frequency Medical Subject Heading (MeSH) terms. A visual matrix was built with the repeated bisection method in gCLUTO software. A social network analysis network was generated with Ucinet 6.0 software and GraphPad Prism 5 software. The analyses demonstrated that in the 6-year period, hot topics were clustered into five categories. As suggested by the constructed strategic diagram, studies related to cytology and physiology were well-developed, whereas those related to neural stem cell applications, tissue engineering, metabolism and cell signaling, and neural stem cell pathology and virology remained immature. Neural stem cell therapy for stroke and Parkinson's disease, the genetics of microRNAs and brain neoplasms, as well as neuroprotective agents, Zika virus, Notch receptor, neural crest and embryonic stem cells were identified as emerging hot spots. These undeveloped themes and popular topics are potential points of focus for new studies on human neural stem cells.
Journal Article
Exploiting behaviors of communities of twitter users for link prediction
Currently, online social networks and social media have become increasingly popular showing an exponential growth. This fact have attracted increasing research interest and, in turn, facilitating the emergence of new interdisciplinary research directions, such as social network analysis. In this scenario, link prediction is one of the most important tasks since it deals with the problem of the existence of a future relation among members in a social network. Previous techniques for link prediction were based on structural (or topological) information. Nevertheless, structural information is not enough to achieve a good performance in the link prediction task on large-scale social networks. Thus, the use of additional information, such as interests or behaviors that nodes have into their communities, may improve the link prediction performance. In this paper, we analyze the viability of using a set of simple and non-expensive techniques that combine structural with community information for predicting the existence of future links in a large-scale online social network, such as Twitter. Twitter, a microblogging service, has emerged as a useful source of informative data shared by millions of users whose relationships require no reciprocation. Twitter network was chosen because it is not well understood, mainly due to the occurrence of directed and asymmetric links yet. Experiments show that our proposals can be used efficiently to improve unsupervised and supervised link prediction task in a directed and asymmetric large-scale network.
Journal Article