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Navigating the Social Maze: An Integrative Review on the Social Network Properties of Deviant Peer Influence in Adolescent Networks

心理学 社会心理学 社会网络分析 社交网络(社会语言学) 发展心理学 社会学 计算机科学 社会化媒体 万维网 社会科学 社会资本
作者
Joke Geeraert,Luis E. C. Rocha,Christophe Vandeviver
出处
期刊:Deviant Behavior [Informa]
卷期号:45 (7): 947-964 被引量:1
标识
DOI:10.1080/01639625.2023.2268791
摘要

ABSTRACTSocial network analysis (SNA) holds great potential for examining the influence of peers and group dynamics on the development of criminal behavior among adolescents as it offers a robust framework for studying complex social interactions. However, there needs to be more knowledge regarding key research findings on deviant adolescent influence using a social network approach. In this integrative literature review, we examine what type of information is used to construct adolescents' social networks, how network compositions affect deviant influence, and how deviant influence is transmitted. For this review, we selected 39 articles by searching Scopus and Web of Science. The results demonstrate that SNA offers valuable insights into the dynamics of deviant peer influence among adolescents. However, there are also conflicting findings that need further exploration. Future research could focus on these discrepancies and continue to leverage the power of SNA in studying the development of criminal behavior in adolescents. This review highlights the importance of SNA in better understanding the mechanisms behind peer influence and provides a roadmap for future research in this field. Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 eij represents the presence or absence of an edge between nodes i and j.2 As α controls the influence of direct links, and β refers to the influence of indirect links, (α+ βcj) represents the weight assigned to each neighbor j. Rij indicates whether a direct link exists between i and j in the network's adjacency matrix.3 \isini represents the eccentricity, which indicates the maximal shortest path length of a node with any other node in the network.4 The full Endnote database can be found here: https://github.com/JokeGeeraert/PhD-project_JokeGeeraertAdditional informationFundingThis work was supported by the Research Foundation – Flanders (FWO) under Grant 1111524N.Notes on contributorsJoke GeeraertJoke Geeraert is a PhD Fellow Fundamental Research of the Research Foundation – Flanders (FWO) at the Department of Criminology, Criminal Law and Social Law, Ghent University, Belgium. Her research concerns social network analyses of co-offending networks to examine the transmission of physical violent offending among offenders.Luis EC RochaLuis E. C. Rocha is a full-time Professor at the Department of Economics and the Department of Physics and Astronomy, Ghent University, Belgium. His main domains of expertise are complex systems, social networks, population dynamics, agent-based models, and social physics.Christophe VandeviverChristophe Vandeviver is a full-time Research Professor of Criminology at the Department of Criminology, Criminal Law and Social Law, Ghent University, Belgium, and affiliated with the Institute for International Research on Criminal Policy (IRCP) and the Netherlands Institute for the Study of Crime and Law Enforcement (NSCR). His research focuses on the spatial and temporal analysis of crime and crime control, crime science, and sexual violence victimization.
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