An Exploratory Analysis Using Co-Authorship Network

2019 ◽  
pp. 166-200
Author(s):  
Burçin Güçlü ◽  
Miguel Ángel Canela ◽  
Inés Alegre
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Organizational Behavior ◽  
Human Behavior ◽  
Online Social Networks ◽  
World Wide ◽  
Academic Research ◽  
E Mail

Social network analysis has been widely used by organizational behavior researchers to stress the importance of the context, social connections, and social structure on human behavior. In the last decade, social network analysis has emerged as one of the most useful techniques for exploring online social networks, world wide web, e-mail traffic, and logistic operations. In this chapter, the authors present an application of social network analysis techniques for academic research. The authors choose Kahneman and Tversky's prospect theory as the focus of their analysis and, based on that, develop a co-authorship structure that depicts in a clear manner the key authors and/or the researchers that dominate and bridge different sub-fields in the field of management. The authors discuss the implications of this study for academic research and management discipline.

New Developments in Social Network Analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniel J. Brass
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Organizational Behavior ◽  
Annual Review ◽  
Publication Date ◽  
Research Directions ◽  
New Research ◽  
Conceptual Foundations

This review of social network analysis focuses on identifying recent trends in interpersonal social networks research in organizations, and generating new research directions, with an emphasis on conceptual foundations. It is organized around two broad social network topics: structural holes and brokerage and the nature of ties. New research directions include adding affect, behavior, and cognition to the traditional structural analysis of social networks, adopting an alter-centric perspective including a relational approach to ego and alters, moving beyond the triad in structural hole and brokerage research to consider alters as brokers, expanding the nature of ties to include negative, multiplex/dissonant, and dormant ties, and exploring the value of redundant ties. The challenge is to answer the question “What's next in social network analysis?” Expected final online publication date for the Annual Review of Organizational Psychology and Organizational Behavior, Volume 9 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Online Social Network Analysis

2019 ◽  
pp. 50-63
Author(s):  
Praveen Kumar Bhanodia ◽  
Aditya Khamparia ◽  
Babita Pandey ◽  
Shaligram Prajapat
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Networks ◽  
Online Social Network ◽  
Structural Features ◽  
Network Properties ◽  
Prediction Systems ◽  
And Behavior

Expansion of online social networks is rapid and furious. Millions of users are appending to it and enriching the nature and behavior, and the information generated has various dimensional properties providing new opportunities and perspective for computation of network properties. The structure of social networks is comprised of nodes and edges whereas users are entities represented by node and relationships designated by edges. Processing of online social networks structural features yields fair knowledge which can be used in many of recommendation and prediction systems. This is referred to as social network analysis, and the features exploited usually are local and global both plays significant role in processing and computation. Local features include properties of nodes like degree of the node (in-degree, out-degree) while global feature process the path between nodes in the entire network. The chapter is an effort in the direction of online social network analysis that explores the basic methods that can be process and analyze the network with a suitable approach to yield knowledge.

Contemporary Gold Rush or Scientific Advancement

2015 ◽  
pp. 210-226
Author(s):  
Darren Quinn ◽  
Liming Chen ◽  
Maurice Mulvenna
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Networks ◽  
Interaction Analysis ◽  
Rapid Evolution ◽  
Gold Rush ◽  
Community Interactions ◽  
The Impact

Following the expansion and mass adoption of Online Social Networks, the impact upon the domain of Social Network Analysis has been a rapid evolution in terms of approach, developing sophisticated methods to capture and understand individual and community interactions. This chapter provides a comprehensive review, examining state-of-the-art Social Network Analysis research and practices, highlighting key trends within the domain. In section 1, the authors examine the growing awareness concerning data as a marketable and scientific commodity. Section 2 reviews the context of Online Social Networking, highlighting key approaches for analysing Online Social Networks. In section 3, they consider modelling motivations of networks, discussing models in line with tie formation approaches. Section 4 outlines data collection approaches along with common structural properties observed in related literature. The authors discuss future directions and emerging approaches, notably semantic social networks and social interaction analysis before conclusions are provided.

A Walk Through Social Network Analysis

2018 ◽  
pp. 1-17
Author(s):  
Atul Srivastava ◽  
Anuradha Pillai ◽  
Dimple Juneja Gupta
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Online Social Networks ◽  
Future Internet ◽  
Distribution Networks ◽  
Content Distribution Networks ◽  
Shared Interest ◽  
Distributed Online Social Networks

Since last more than forty years, social network analysis (SNA) techniques have evolved as one of the successful applications of Internet. Numerous reasons demand better understanding of the structure of social networks, need of their analysis and their impact on future Internet and society. For instance, finding the shared interest and trust could be one of the reasons to study social networks. Moreover, if in future, distributed online social networks are popular and bandwidth intensive, they can have a significant impact on Internet traffic, just as current peer-to-peer content distribution networks do. Regardless of one's stance on these phenomena, a better understanding of the structure of social networks is likely to improve our understanding of the opportunities, limitations and threats associated with these ideas. For instance, gigantic size of online social networks, their dynamic behavior, clustering and privacy policies held by users are some of the major challenges. This chapter presents an engraved review spanning from need of SNA to the implications associated with it.

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.

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