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Bots are less central than verified accounts during contentious political events

Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of inf...

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Detalles Bibliográficos
Autores principales: González-Bailón, Sandra, De Domenico, Manlio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980437/
https://www.ncbi.nlm.nih.gov/pubmed/33836572
http://dx.doi.org/10.1073/pnas.2013443118
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author González-Bailón, Sandra
De Domenico, Manlio
author_facet González-Bailón, Sandra
De Domenico, Manlio
author_sort González-Bailón, Sandra
collection PubMed
description Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity.
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spelling pubmed-79804372021-03-26 Bots are less central than verified accounts during contentious political events González-Bailón, Sandra De Domenico, Manlio Proc Natl Acad Sci U S A Social Sciences Information manipulation is widespread in today’s media environment. Online networks have disrupted the gatekeeping role of traditional media by allowing various actors to influence the public agenda; they have also allowed automated accounts (or bots) to blend with human activity in the flow of information. Here, we assess the impact that bots had on the dissemination of content during two contentious political events that evolved in real time on social media. We focus on events of heightened political tension because they are particularly susceptible to information campaigns designed to mislead or exacerbate conflict. We compare the visibility of bots with human accounts, verified accounts, and mainstream news outlets. Our analyses combine millions of posts from a popular microblogging platform with web-tracking data collected from two different countries and timeframes. We employ tools from network science, natural language processing, and machine learning to analyze the diffusion structure, the content of the messages diffused, and the actors behind those messages as the political events unfolded. We show that verified accounts are significantly more visible than unverified bots in the coverage of the events but also that bots attract more attention than human accounts. Our findings highlight that social media and the web are very different news ecosystems in terms of prevalent news sources and that both humans and bots contribute to generate discrepancy in news visibility with their activity. National Academy of Sciences 2021-03-16 2021-03-08 /pmc/articles/PMC7980437/ /pubmed/33836572 http://dx.doi.org/10.1073/pnas.2013443118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
González-Bailón, Sandra
De Domenico, Manlio
Bots are less central than verified accounts during contentious political events
title Bots are less central than verified accounts during contentious political events
title_full Bots are less central than verified accounts during contentious political events
title_fullStr Bots are less central than verified accounts during contentious political events
title_full_unstemmed Bots are less central than verified accounts during contentious political events
title_short Bots are less central than verified accounts during contentious political events
title_sort bots are less central than verified accounts during contentious political events
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7980437/
https://www.ncbi.nlm.nih.gov/pubmed/33836572
http://dx.doi.org/10.1073/pnas.2013443118
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