scholarly journals Trends and perspectives on the use of social network analysis in behavioural ecology: a bibliometric approach

2018 ◽  
Author(s):  
Quinn M.R. Webber ◽  
Eric Vander Wal
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Temporal Trends ◽  
Future Research ◽  
Network Research ◽  
Emerging Trends ◽  
Primary Finding ◽  
Over Time

AbstractThe increased popularity and improved accessibility of social network analysis has improved our ability to test hypotheses about the complexity of animal social structure. To gain a deeper understanding of the use and application of social network analysis, we systematically surveyed the literature and extracted information on publication trends from articles using social network analysis. We synthesize trends in social network research over time and highlight variation in the use of different aspects of social network analysis. Our primary finding highlights the increase in use of social network analysis over time and from this finding, we observed an increase in the number of review and methods of social network analysis. We also found that most studies included a relatively small number (median = 15, range = 4–1406) of individuals to generate social networks, while the number and type of social network metrics calculated in a given study varied zero to nine (median = 2, range 0–9). The type of data collection or the software programs used to analyze social network data have changed; SOCPROG and UCINET have been replaced by various R packages over time. Finally, we found strong taxonomic and conservation bias in the species studied using social network analysis. Most species studied using social networks are mammals (111/201, 55%) or birds (47/201, 23%) and the majority tend to be species of least concern (119/201, 59%). We highlight emerging trends in social network research that may be valuable for distinct groups of social network researchers: students new to social network analysis, experienced behavioural ecologists interested in using social network analysis, and advanced social network users interested in trends of social network research. In summary we address the temporal trends in social network publication practices, highlight potential bias in some of the ways we employ social network analysis, and provide recommendations for future research based on our findings.

scholarly journals Social Network Analysis Visualization

2015 ◽  
pp. 257-270
Author(s):  
Mohana Shanmugam ◽  
Yusmadi Yah Jusoh ◽  
Rozi Nor Haizan Nor ◽  
Marzanah A. Jabar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Network ◽  
Future Research ◽  
Research Gaps ◽  
The Social ◽  
Network Studies ◽  
Academic Study

The social network surge has become a mainstream subject of academic study in a myriad of disciplines. This chapter posits the social network literature by highlighting the terminologies of social networks and details the types of tools and methodologies used in prior studies. The list is supplemented by identifying the research gaps for future research of interest to both academics and practitioners. Additionally, the case of Facebook is used to study the elements of a social network analysis. This chapter also highlights past validated models with regards to social networks which are deemed significant for online social network studies. Furthermore, this chapter seeks to enlighten our knowledge on social network analysis and tap into the social network capabilities.

How to Study Online Networking

2022 ◽  
pp. 360-374
Author(s):  
Fabio Corbisiero
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Dissemination ◽  
Field Research ◽  
Social Phenomena ◽  
The Past ◽  
Network Research

Social media and social networks are pervasive in the daily use as well as in a number of applications. Social media and social networks are also intertwined, as the social medial platforms also offer the opportunity to develop and analyze social networks. Over the past two decades, there has been an explosion of interest in network research through social network analysis. Network research is “warm” today, with the number of articles on the topic of social media and social networks nearly tripling in the past decade. This interweaving has been a further breakthrough within field research yielding explanations for social phenomena in a wide variety of new ways. Social network analysis (SNA) has been recognized as a powerful tool for representing social network structures and information dissemination on the web. Here, the authors review the kinds of things that sociologists have tried to explain using social network analysis and provide a nutshell description of the basic assumptions, goals, and explanatory mechanisms prevalent in the field, with emphasis on SNA research methodology.

Analysis of Online Social Networks for the Identification of Sarcasm

2018 ◽  
pp. 92-105 ◽  
Author(s):  
Pulkit Mehndiratta
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Sentiment Analysis ◽  
Online Social Networks ◽  
Future Research ◽  
Research Directions ◽  
Textual Data ◽  
Future Research Directions

With the ever-increasing acceptance of online social networks (OSNs), a new dimension has evolved for communication amongst humans. OSNs have given us the opportunity to monitor and mine the opinions of a large number of online active populations in real time. Many diverse approaches have been proposed, various datasets have been generated, but there is a need of collective understanding of this area. Researchers are working around the globe to find a pattern to judge the mood of the user; the still serious problem of detection of irony and sarcasm in textual data poses a threat to the accuracy of the techniques evolved till date. This chapter aims to help the reader to think and learn more clearly about the aspects of sentiment analysis, social network analysis, and detection of irony or sarcasm in textual data generated via online social networks. It argues and discusses various techniques and solutions available in literature currently. In the end, the chapter provides some answers to the open-ended question and future research directions related to the analysis of textual data.

Introduction

2020 ◽  
pp. xxii-13
Author(s):  
Ryan Light ◽  
James Moody
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Bibliometric Analysis ◽  
Social Life ◽  
New Directions ◽  
Central Paradigm

This chapter provides an introduction to this volume on social networks. It argues that social network analysis is greater than a method or data, but serves as a central paradigm for understanding social life. The chapter offers evidence of the influence of social network analysis with a bibliometric analysis of research on social networks. This analysis underscores how pervasive network analysis has become and highlights key theoretical and methodological concerns. It also introduces the sections of the volume broadly structured around theory, methods, broad conceptualizations like culture and temporality, and disciplinary contributions. The chapter concludes by discussing several promising new directions in the field of social network analysis.

The Oxford Handbook of Social Networks

2020 ◽  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Life ◽  
Information Science ◽  
Computational Social Science ◽  
The Social ◽  
Diverse Field ◽  
The Rich

Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others.

scholarly journals Nursing Students’ Subjective Happiness: A Social Network Analysis

2021 ◽  
Vol 18 (21) ◽  
pp. 11612
Author(s):  
Eun-Joo Kim ◽  
Ji-Young Lim ◽  
Geun-Myun Kim ◽  
Seong-Kwang Kim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Nursing Students ◽  
Network Analysis ◽  
Group Dynamics ◽  
Future Research ◽  
Subjective Happiness ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
High Level

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.

scholarly journals Hacia la complejidad por la vía de las redes. Nuevas lecciones epistemológicas

2014 ◽  
Author(s):  
Carlos Reynoso
Keyword(s):  
Social Sciences ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scale Free Network ◽  
New Paradigm ◽  
Scale Free ◽  
Network Research ◽  
Free Network

This paper sur veys the reciprocal impacts between Social Network Analysis and the new paradigm of complexity and chaos theories, as well as the emergence of scale-free network research in the twenty-first centur y. This study is embedded in the context of a histor y of the most momentous events in network theor y and practice , from Euler to Barabási, used as a star ting point to interrogate some critical epistemological issues from the viewpoint of contemporar y social sciences.

Predicting Violent Victimization Using Social Network Analysis From Police Data

2021 ◽  
Vol 36 (3) ◽  
pp. 436-454
Author(s):  
Andrew M. Fox ◽  
Kenneth J. Novak ◽  
Tinneke Van Camp ◽  
Chadley James
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Violent Crime ◽  
Violent Victimization ◽  
Crime Victimization ◽  
Effective Prevention ◽  
Police Data ◽  
Assault Victims

Extant research suggests that membership in crime networks explains vulnerability to violent crime victimization. Consequently, identifying deviant social networks and understanding their structure and individual members' role in them could provide insight into victimization risk. Identifying social networks may help tailor crime prevention strategies to mitigate victimization risks and dismantle deviant networks. Social network analysis (SNA) offers a particular means of comprehending and measuring such group-level structures and the roles that individuals play within them. When applied to research on crime and victimization, it could provide a foundation for developing precise, effective prevention, intervention, and suppression strategies. This study uses police data to examine whether individuals most central to a deviant social network are those who are most likely to become victims of violent crime, and which crime network roles are most likely to be associated with vulnerability to violent victimization. SNA of these data indicates that network individuals who are in a position to manage the flow of information in the network (betweenness centrality), regardless of their number of connections (degree centrality), are significantly more likely to be homicide and aggravated assault victims. Implications for police practice are discussed.

Entanglement, Materiality and the Social Organisation of Construction Workers in Classical Athens

2018 ◽  
pp. 512-528
Author(s):  
Diane Harris Cline
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Theory ◽  
Actor Network Theory ◽  
Fifth Century ◽  
Actor Network ◽  
The Social ◽  
Building Program

This chapter views the “Periclean Building Program” through the lens of Actor Network Theory, in order to explore the ways in which the construction of these buildings transformed Athenian society and politics in the fifth century BC. It begins by applying some Actor Network Theory concepts to the process that was involved in getting approval for the building program as described by Thucydides and Plutarch in his Life of Pericles. Actor Network Theory blends entanglement (human-material thing interdependence) with network thinking, so it allows us to reframe our views to include social networks when we think about the political debate and social tensions in Athens that arose from Pericles’s proposal to construct the Parthenon and Propylaea on the Athenian Acropolis, the Telesterion at Eleusis, the Odeon at the base of the South slope of the Acropolis, and the long wall to Peiraeus. Social Network Analysis can model the social networks, and the clusters within them, that existed in mid-fifth century Athens. By using Social Network Analysis we can then show how the construction work itself transformed a fractious city into a harmonious one through sustained, collective efforts that engaged large numbers of lower class citizens, all responding to each other’s needs in a chaine operatoire..

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