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The evolution of online ideological communities
Online communities are virtual spaces for users to share interests, support others, and to exchange knowledge and information. Understanding user behavior is valuable to organizations and has applications from marketing to security, for instance, identifying leaders within a community or predicting...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530841/ https://www.ncbi.nlm.nih.gov/pubmed/31116767 http://dx.doi.org/10.1371/journal.pone.0216932 |
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author | Davidson, Brittany I. Jones, Simon L. Joinson, Adam N. Hinds, Joanne |
author_facet | Davidson, Brittany I. Jones, Simon L. Joinson, Adam N. Hinds, Joanne |
author_sort | Davidson, Brittany I. |
collection | PubMed |
description | Online communities are virtual spaces for users to share interests, support others, and to exchange knowledge and information. Understanding user behavior is valuable to organizations and has applications from marketing to security, for instance, identifying leaders within a community or predicting future behavior. In the present research, we seek to understand the various roles that users adopt in online communities–for instance, who leads the conversation? Who are the supporters? We examine user role changes over time and the pathways that users follow. This allows us to explore the differences between users who progress to leadership positions and users who fail to develop influence. We also reflect on how user role proportions impact the overall health of the community. Here, we examine two online ideological communities, RevLeft and Islamic Awakening (N = 1631; N = 849), and provide a novel approach to identify various types of users. Finally, we study user role trajectories over time and identify community “leaders” from meta-data alone. Study One examined both communities using K-MEANS cluster analysis of behavioral meta-data, which revealed seven user roles. We then mapped these roles against Preece and Schneiderman’s (2009) Reader-to-Leader Framework (RtLF). Both communities aligned with the RtLF, where most users were “contributors”, many were “collaborators”, and few were “leaders”. Study Two looked at one community over a two-year period and found that, despite a high churn rate of users, roles were stable over time. We built a model of user role transitions over the two years. This can be used to predict user role changes in the future, which will have implications for community managers and security focused contexts (e.g., analyzing behavioral meta-data from forums and websites known to be associated with illicit activity). |
format | Online Article Text |
id | pubmed-6530841 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-65308412019-05-31 The evolution of online ideological communities Davidson, Brittany I. Jones, Simon L. Joinson, Adam N. Hinds, Joanne PLoS One Research Article Online communities are virtual spaces for users to share interests, support others, and to exchange knowledge and information. Understanding user behavior is valuable to organizations and has applications from marketing to security, for instance, identifying leaders within a community or predicting future behavior. In the present research, we seek to understand the various roles that users adopt in online communities–for instance, who leads the conversation? Who are the supporters? We examine user role changes over time and the pathways that users follow. This allows us to explore the differences between users who progress to leadership positions and users who fail to develop influence. We also reflect on how user role proportions impact the overall health of the community. Here, we examine two online ideological communities, RevLeft and Islamic Awakening (N = 1631; N = 849), and provide a novel approach to identify various types of users. Finally, we study user role trajectories over time and identify community “leaders” from meta-data alone. Study One examined both communities using K-MEANS cluster analysis of behavioral meta-data, which revealed seven user roles. We then mapped these roles against Preece and Schneiderman’s (2009) Reader-to-Leader Framework (RtLF). Both communities aligned with the RtLF, where most users were “contributors”, many were “collaborators”, and few were “leaders”. Study Two looked at one community over a two-year period and found that, despite a high churn rate of users, roles were stable over time. We built a model of user role transitions over the two years. This can be used to predict user role changes in the future, which will have implications for community managers and security focused contexts (e.g., analyzing behavioral meta-data from forums and websites known to be associated with illicit activity). Public Library of Science 2019-05-22 /pmc/articles/PMC6530841/ /pubmed/31116767 http://dx.doi.org/10.1371/journal.pone.0216932 Text en © 2019 Davidson et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Davidson, Brittany I. Jones, Simon L. Joinson, Adam N. Hinds, Joanne The evolution of online ideological communities |
title | The evolution of online ideological communities |
title_full | The evolution of online ideological communities |
title_fullStr | The evolution of online ideological communities |
title_full_unstemmed | The evolution of online ideological communities |
title_short | The evolution of online ideological communities |
title_sort | evolution of online ideological communities |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530841/ https://www.ncbi.nlm.nih.gov/pubmed/31116767 http://dx.doi.org/10.1371/journal.pone.0216932 |
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