Consensus Dynamics in Online Collaboration Networks

Research output: ThesisDoctoral ThesisResearch

Abstract

In many real-world settings, it is essential for a group of interacting individuals to reach shared understanding and consensus on a given issue. Consensus can strengthen groups and their impact on society. The popularity of online social and collaboration networks has influenced the way individuals interact with each other. Many collaboration sites (i.e., StackExchange, Reddit or Wikipedia) enable users to exchange opinions, discuss certain topics and solve problems while interacting with other online users. This thesis aims at uncovering the dynamics of consensus building among users collaborating online. Consensus dynamics is closely related to the process of opinion dynamics. Opinion dynamics has been studied from the perspective of social sciences, physics, mathematics, complex system studies and network science. However, such studies often remain confined to these disciplines. Therefore, this thesis applies an interdisciplinary approach. It builds hypotheses based on social science theories, simulates
opinion dynamics utilizing agent-based models from statistical physics and applies social network analysis on empirical datasets extracted from the Web. Methodologically, this thesis contributes a novel framework to study the role and interplay of some of the main factors in consensus building (i.e., users social status, network structure, users similarity and content creation). The presented method can be applied to run extensive simulations of opinion dynamics in arbitrary collaboration networks. The empirical findings of this thesis help draw recommendations on how to integrate the influence of user characteristics (e.g., social status) in opinion dynamics to optimize consensus building. Additionally, this thesis experimentally demonstrates how content dynamics drives the process of agreement and disagreement between users collaborating online. These results add to our understanding of the challenges of designing and implementing services that promote consensus building.
Original languageEnglish
QualificationDoctor of Technology
Awarding Institution
  • Graz University of Technology (90000)
Supervisors/Advisors
  • Helic, Denis, Supervisor
  • Lex, Elisabeth, Advisor
Publication statusPublished - Jan 2019

Fingerprint

Social sciences
Physics
Electric network analysis
Large scale systems

Keywords

  • Consensus Building
  • Opinion Dynamics
  • Content Dynamics
  • Agent-Based Models
  • Online Collaboration Networks
  • Social Influence
  • Social Science
  • Statistical Physics
  • Mathematical Models
  • Complexity Studies
  • Network Science
  • Social Network Analysis
  • Computational Social Science
  • Q&A Sites
  • StackExchange
  • Reddit
  • Wikipedia
  • Co-Authorship Networks

Cite this

Consensus Dynamics in Online Collaboration Networks. / Hasani-Mavriqi, Ilire.

2019. 208 p.

Research output: ThesisDoctoral ThesisResearch

Hasani-Mavriqi, I 2019, 'Consensus Dynamics in Online Collaboration Networks', Doctor of Technology, Graz University of Technology (90000).
@phdthesis{7a8d2869d0aa41949feea91a5c9acbcd,
title = "Consensus Dynamics in Online Collaboration Networks",
abstract = "In many real-world settings, it is essential for a group of interacting individuals to reach shared understanding and consensus on a given issue. Consensus can strengthen groups and their impact on society. The popularity of online social and collaboration networks has influenced the way individuals interact with each other. Many collaboration sites (i.e., StackExchange, Reddit or Wikipedia) enable users to exchange opinions, discuss certain topics and solve problems while interacting with other online users. This thesis aims at uncovering the dynamics of consensus building among users collaborating online. Consensus dynamics is closely related to the process of opinion dynamics. Opinion dynamics has been studied from the perspective of social sciences, physics, mathematics, complex system studies and network science. However, such studies often remain confined to these disciplines. Therefore, this thesis applies an interdisciplinary approach. It builds hypotheses based on social science theories, simulatesopinion dynamics utilizing agent-based models from statistical physics and applies social network analysis on empirical datasets extracted from the Web. Methodologically, this thesis contributes a novel framework to study the role and interplay of some of the main factors in consensus building (i.e., users social status, network structure, users similarity and content creation). The presented method can be applied to run extensive simulations of opinion dynamics in arbitrary collaboration networks. The empirical findings of this thesis help draw recommendations on how to integrate the influence of user characteristics (e.g., social status) in opinion dynamics to optimize consensus building. Additionally, this thesis experimentally demonstrates how content dynamics drives the process of agreement and disagreement between users collaborating online. These results add to our understanding of the challenges of designing and implementing services that promote consensus building.",
keywords = "Consensus Building, Opinion Dynamics, Content Dynamics, Agent-Based Models, Online Collaboration Networks, Social Influence, Social Science, Statistical Physics, Mathematical Models, Complexity Studies, Network Science, Social Network Analysis, Computational Social Science, Q&A Sites, StackExchange, Reddit, Wikipedia, Co-Authorship Networks",
author = "Ilire Hasani-Mavriqi",
year = "2019",
month = "1",
language = "English",
school = "Graz University of Technology (90000)",

}

TY - THES

T1 - Consensus Dynamics in Online Collaboration Networks

AU - Hasani-Mavriqi, Ilire

PY - 2019/1

Y1 - 2019/1

N2 - In many real-world settings, it is essential for a group of interacting individuals to reach shared understanding and consensus on a given issue. Consensus can strengthen groups and their impact on society. The popularity of online social and collaboration networks has influenced the way individuals interact with each other. Many collaboration sites (i.e., StackExchange, Reddit or Wikipedia) enable users to exchange opinions, discuss certain topics and solve problems while interacting with other online users. This thesis aims at uncovering the dynamics of consensus building among users collaborating online. Consensus dynamics is closely related to the process of opinion dynamics. Opinion dynamics has been studied from the perspective of social sciences, physics, mathematics, complex system studies and network science. However, such studies often remain confined to these disciplines. Therefore, this thesis applies an interdisciplinary approach. It builds hypotheses based on social science theories, simulatesopinion dynamics utilizing agent-based models from statistical physics and applies social network analysis on empirical datasets extracted from the Web. Methodologically, this thesis contributes a novel framework to study the role and interplay of some of the main factors in consensus building (i.e., users social status, network structure, users similarity and content creation). The presented method can be applied to run extensive simulations of opinion dynamics in arbitrary collaboration networks. The empirical findings of this thesis help draw recommendations on how to integrate the influence of user characteristics (e.g., social status) in opinion dynamics to optimize consensus building. Additionally, this thesis experimentally demonstrates how content dynamics drives the process of agreement and disagreement between users collaborating online. These results add to our understanding of the challenges of designing and implementing services that promote consensus building.

AB - In many real-world settings, it is essential for a group of interacting individuals to reach shared understanding and consensus on a given issue. Consensus can strengthen groups and their impact on society. The popularity of online social and collaboration networks has influenced the way individuals interact with each other. Many collaboration sites (i.e., StackExchange, Reddit or Wikipedia) enable users to exchange opinions, discuss certain topics and solve problems while interacting with other online users. This thesis aims at uncovering the dynamics of consensus building among users collaborating online. Consensus dynamics is closely related to the process of opinion dynamics. Opinion dynamics has been studied from the perspective of social sciences, physics, mathematics, complex system studies and network science. However, such studies often remain confined to these disciplines. Therefore, this thesis applies an interdisciplinary approach. It builds hypotheses based on social science theories, simulatesopinion dynamics utilizing agent-based models from statistical physics and applies social network analysis on empirical datasets extracted from the Web. Methodologically, this thesis contributes a novel framework to study the role and interplay of some of the main factors in consensus building (i.e., users social status, network structure, users similarity and content creation). The presented method can be applied to run extensive simulations of opinion dynamics in arbitrary collaboration networks. The empirical findings of this thesis help draw recommendations on how to integrate the influence of user characteristics (e.g., social status) in opinion dynamics to optimize consensus building. Additionally, this thesis experimentally demonstrates how content dynamics drives the process of agreement and disagreement between users collaborating online. These results add to our understanding of the challenges of designing and implementing services that promote consensus building.

KW - Consensus Building

KW - Opinion Dynamics

KW - Content Dynamics

KW - Agent-Based Models

KW - Online Collaboration Networks

KW - Social Influence

KW - Social Science

KW - Statistical Physics

KW - Mathematical Models

KW - Complexity Studies

KW - Network Science

KW - Social Network Analysis

KW - Computational Social Science

KW - Q&A Sites

KW - StackExchange

KW - Reddit

KW - Wikipedia

KW - Co-Authorship Networks

M3 - Doctoral Thesis

ER -