Consensus Dynamics in Online Collaboration Networks

Publikation: StudienabschlussarbeitDissertationForschung

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.
Spracheenglisch
QualifikationDoktor der Technik
Gradverleihende Hochschule
  • Technische Universität Graz (90000)
Betreuer/-in / Berater/-in
  • Helic, Denis, Betreuer
  • Lex, Elisabeth, Berater
StatusVeröffentlicht - Jan 2019

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Social sciences
Physics
Electric network analysis
Large scale systems

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

    2019. 208 S.

    Publikation: StudienabschlussarbeitDissertationForschung

    Hasani-Mavriqi, I 2019, 'Consensus Dynamics in Online Collaboration Networks', Doktor der Technik, Technische Universität Graz (90000).
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    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.",
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    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.

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    KW - Mathematical Models

    KW - Complexity Studies

    KW - Network Science

    KW - Social Network Analysis

    KW - Computational Social Science

    KW - Q&A Sites

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    KW - Reddit

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