Criminal Networks

2020 ◽  
pp. 615-632
Author(s):  
Chris M. Smith ◽  
Andrew V. Papachristos
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Criminal Behavior ◽  
Theoretical Orientations ◽  
Criminal Networks ◽  
Future Directions ◽  
Criminal Organizations ◽  
Criminal Groups

Social network analysis identifies and explains criminal behavior and criminal groups as an outcome of social relationships that are structured beyond the characteristics of individuals engaged in crime. This chapter takes stock of research using social network analysis to study criminal organizations and groups of criminals, considers the innovations in measuring criminal groups, discusses the limitations of criminal network data, and classifies theoretical orientations used in the field. The chapter discusses the implications of criminal networks research on policy and intervention efforts. The chapter concludes with a proposal for future directions to advance inquiry into criminal networks.

Duality beyondPersons and Groups

2020 ◽  
pp. 391-413
Author(s):  
Sophie Mützel ◽  
Ronald Breiger
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Data ◽  
Future Directions ◽  
Affiliation Networks ◽  
The Social ◽  
Recent Developments ◽  
Principle Of Duality ◽  
Seminal Article

This chapter focuses on the general principle of duality, which was originally introduced by Simmel as the intersection of social circles. In a seminal article, Breiger formalized Simmel’s idea, showing how two-mode types of network data can be transformed into one-mode networks. This formal translation proved to be fundamental for social network analysis, which no longer needed data on who interacted with whom but could work with other types of data. In turn, it also proved fundamental for the analysis of how the social is structured in general, as many relations are dual (e.g. persons and groups, authors and articles, organizations and practices), and are thus susceptible to an analysis according to duality principles. The chapter locates the concept of duality within past and present sociology. It also discusses the use of duality in the analysis of culture as well as in affiliation networks. It closes with recent developments and future directions.

The evolution of the intellectual structure of strategic management between 1980 and 2019

2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Strategic Management ◽  
Citation Analysis ◽  
Intellectual Structure ◽  
Future Directions ◽  
Content Type ◽  
The Social ◽  
Economic Foundation

PurposeThe authors evaluate the evolution of the intellectual structure of strategic management (SM) by employing a document co-citation analysis through a network analysis for academic citations in articles published in the Strategic Management Journal (SMJ).Design/methodology/approachThe authors employed the co-citation analysis through the social network analysis.FindingsThe authors outlined the evolution of the academic foundations of the structure and emphasized several domains. The economic foundation of SM research with macro and micro perspectives has generated a solid knowledge stock in the literature. Industrial organization (IO) psychology has also been another dominant foundation. Its robust development and extension in the literature have focused on cognitive issues in actors' behaviors as a behavioral foundation of SM. Methodological issues in SM research have become dominant between 2004 and 2011, but their influence has been inconsistent. The authors concluded by recommending future directions to increase maturity in the SM research domain.Originality/valueThis is the first paper to elucidate the intellectual structure of SM by adopting the co-citation analysis through the social network analysis.

Social Network Analysis in Marketing

E-Marketing ◽  
2012 ◽  
pp. 185-197
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

Web Mining and Social Network Analysis

Data Mining ◽  
2013 ◽  
pp. 326-335
Author(s):  
Roberto Marmo
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Web Mining ◽  
Social Network Mining ◽  
Data Mining Algorithms ◽  
Instant Messenger ◽  
Mining Algorithms

Research on social networks has advanced significantly due to wide variety of on-line social websites and very popular Web 2.0 application. Social network analysis views social relationships in terms of network and graph theory about nodes (individual actors within the network) and ties (relationships between the actors). Using web mining techniques and social networks analysis it is possible to process and analyze large amount of social data (such as blogtagging, online game playing, instant messenger etc.) and by this to discover valuable information from data. In this way, we can understand the social structure, social relationships and social behaviors. This new approach is also denoted as social network mining. These algorithms differ from established set of data mining algorithms developed to analyze individual records, because social network datasets are called relational due to centrality of relations among entities. This chapter also sets out a process to apply web mining.

Social Network Analysis in Marketing

2011 ◽  
pp. 271-283
Author(s):  
Przemyslaw Kazienko ◽  
Piotr Doskocz ◽  
Tomasz Kajdanowicz
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Network Data ◽  
Social Network Data ◽  
The Social ◽  
Targeted Marketing ◽  
Potential Customers ◽  
Demographic Features

The chapter describes a method how to perform a classification task without any demographic features and based only on the social network data. The concept of such collective classification facilitates to identify potential customers by means of services used or products purchased by the current customers, i.e. classes they belong to as well as using social relationships between the known and potential customers. As a result, a personalized offer can be prepared for the new clients. This innovative marketing method can boost targeted marketing campaigns.

scholarly journals Lengthy leader male tenure delays male offspring dispersal in a primate multilevel society

Behaviour ◽  
2019 ◽  
Vol 156 (13-14) ◽  
pp. 1371-1391
Author(s):  
Gu Fang ◽  
Xiao-Min Gao ◽  
Dong Zhang ◽  
Derek Dunn ◽  
Ruliang Pan ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Kin Selection ◽  
World Monkey ◽  
Male Offspring ◽  
Monkey Species ◽  
Male Dispersal ◽  
Multilevel Society

Abstract Natal dispersals are male-biased in most Old World monkey species, especially those that are polygynous. We examined patterns of male dispersal in golden snub-nosed monkeys, in which male offspring mainly disperse as juveniles from their natal one-male units (OMUs) to a bachelor group. However, out of a total of 112 male dispersals from 2001–2016, we documented six cases in which male offspring remained in their natal OMU until sub-adulthood. Based on monitoring of dispersal dynamics, we found that male offspring were more likely to delay dispersal if the tenure of leader males was lengthy. Social network analysis showed male offspring who delayed dispersal exhibited strong social relationships with each other and their OMU leader male but not with the females of their OMU. Our results suggest that the length of leader male tenure may affect natal male dispersal due to benefits to leader males accrued via intrasexual competition and kin selection.

Social Network Analysis in Egyptology: Benefits, Methods and Limits

2019 ◽  
Vol 105 (1) ◽  
pp. 83-96
Author(s):  
Vincent Chollier
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Empirical Method ◽  
Ancient Egypt ◽  
Centrality Measures ◽  
Defining Relations ◽  
The Family ◽  
Kinship Terminology

This article aims at presenting a methodology for Social Network Analysis (SNA) applied to Egyptology and ancient societies studies, with its benefits and issues. One of the big issues dealing with social relationships in ancient Egypt lies in the use of kinship terminology defining relations outside the family. In that sense, SNA allows researchers to partially set aside links values contrary to traditional genealogical studies, especially for the graphical projection. Thus, biological and social brothers do not have to be distinguished using this method, although this distinction is often impossible to do. It then presents an empirical method developed using this branch of sociology on an Egyptological dataset dating back from the New Kingdom. With the help of centrality measures, SNA enabled attention to be drawn to secondary role characters at the first sight of the hieroglyphic documentation. However, studying such a type of documentation requires a cautious approach, especially regarding the nature and aim of the sources available.

scholarly journals Linking Quantitative and Qualitative Network Approaches: A Review of Mixed Methods Social Network Analysis in Education Research

2020 ◽  
Vol 44 (1) ◽  
pp. 244-268 ◽  
Author(s):  
Dominik E. Froehlich ◽  
Sara Van Waes ◽  
Hannah Schäfer
Keyword(s):  
Education Research ◽  
Social Network ◽  
Mixed Methods ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Relationships ◽  
Mixed Methods Research ◽  
Qualitative Approaches ◽  
Research Questions ◽  
Network Approaches

Social network analysis (SNA) is becoming a prevalent method in education research and practice. But criticism has been voiced against the heavy reliance on quantification within SNA. Recent work suggests combining quantitative and qualitative approaches in SNA—mixed methods social network analysis (MMSNA)—as a remedy. MMSNA is helpful for addressing research questions related to the formal or structural side of relationships and networks, but it also attends to more qualitative questions such as the meaning of interactions or the variability of social relationships. In this chapter, we describe how researchers have applied and presented MMSNA in publications from the perspective of general mixed methods research. Based on a systematic review, we summarize the different applications within the field of education and learning research, point to potential shortcomings of the methods and its presentation, and develop an agenda to support researchers in conducting future MMSNA research.

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