scholarly journals BISoN: A Bayesian Framework for Inference of Social Networks

2021 ◽  
Author(s):  
Jordan D. A. Hart ◽  
Michael N. Weiss ◽  
Daniel W. Franks ◽  
Lauren J. N. Brent
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Observational Data ◽  
Bayesian Framework ◽  
Social Data ◽  
Association Tests ◽  
Point Estimates ◽  
Network Properties

Social networks are often constructed from point estimates of edge weights. In many contexts, edge weights are inferred from observational data, and the uncertainty around point estimates can be affected by various factors. Though this has been acknowledged in previous work, methods that explicitly quantify uncertainty in edge weights have not yet been widely adopted, and remain undeveloped for common types of data. Furthermore, existing methods are unable to cope with some of the complexities often found in observational data, and do not propagate uncertainty in edge weights to subsequent analyses. We introduce a unified Bayesian framework for modelling social networks based on observational data. This framework, which we call BISoN, can accommodate many common types of observational social data, can capture confounds and model effects at the level of observations, and is fully compatible with popular methods of social network analysis. We show how the framework can be applied to common types of data and how various types of downstream analyses can be performed, including non-random association tests and regressions on network properties. Our framework opens up the opportunity to test new types of hypotheses, make full use of observational datasets, and increase the reliability of scientific inferences. We have made example R code available to enable adoption of the framework.

scholarly journals Measuring the value of the social network: analysis, quantitative approach, and application

2015 ◽  
Author(s):  
Sujata Jindal ◽  
Ritu Sindhu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Impact ◽  
Quantitative Approach ◽  
Social Data ◽  
The Social ◽  
The Impact ◽  
Day By Day

Social networks are growing day by day. Users of the social networks are generating values for these networks. All the users can’t be considered equal as they have different social network impact value. In this paper we analyze the social impact of a user and propose a method to estimate an individual’s worth to a social network in terms of impact. The mathematical evaluations show the effectiveness of our method. Based on the proposed method many applications can be built taking into consideration the impact any individual’s social profile has. We have tried to make various social data attributes more valuable and meaningful.

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.

scholarly journals Measuring the value of the social network: analysis, quantitative approach, and application

2015 ◽  
Author(s):  
Sujata Jindal ◽  
Ritu Sindhu
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Impact ◽  
Quantitative Approach ◽  
Social Data ◽  
The Social ◽  
The Impact ◽  
Day By Day

Social networks are growing day by day. Users of the social networks are generating values for these networks. All the users can’t be considered equal as they have different social network impact value. In this paper we analyze the social impact of a user and propose a method to estimate an individual’s worth to a social network in terms of impact. The mathematical evaluations show the effectiveness of our method. Based on the proposed method many applications can be built taking into consideration the impact any individual’s social profile has. We have tried to make various social data attributes more valuable and meaningful.

scholarly journals A multilevel statistical toolkit to study animal social networks: Animal Network Toolkit (ANT) R package

2018 ◽  
Author(s):  
Sosa Sebastian ◽  
Puga-Gonzalez Ivan ◽  
Hu Feng He ◽  
Zhang Peng ◽  
Xiaohua Xie ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
R Package ◽  
Interaction Patterns ◽  
Network Properties ◽  
New Methodologies ◽  
The Many ◽  
Animal Social Networks

AbstractHow animals interact and develop social relationships regarding, individual attributes, sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis, allow us to elucidate these types of questions. However, the different methodologies developed to that end and the speed at which they emerge make their use difficult. Moreover, the lack of communication between the different software developed to provide an answer to the same/different research questions is a source of confusion. The R package Animal Network Toolkit (ANT) was developed with the aim of implementing in one package the many different social network analysis techniques currently used in the study of animal social networks. Hence, ANT is a toolkit for animal research allowing among other things to: 1) measure global, dyadic and nodal networks metrics; 2) perform data randomization: pre-network and network (node and link) permutations; 3) perform statistical permutation tests. The package is partially coded in C++ for an optimal coding speed, and it gives researchers a workflow from raw data to the achievement of statistical analyses, allowing for a multilevel approach: from individual position and role within the network, to the identification of interaction patterns, and the analysis of the overall network properties.

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 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.

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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