Competition for popularity and interventions on a Chinese microblogging site
Microblogging sites are important vehicles for the users to obtain information and shape public opinion thus they are arenas of continuous competition for popularity. Most popular topics are usually indicated on ranking lists. In this study, we investigate the public attention dynamics through the H...
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Published in | PloS one Vol. 18; no. 5; p. e0286093 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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United States
Public Library of Science
23.05.2023
Public Library of Science (PLoS) |
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Abstract | Microblogging sites are important vehicles for the users to obtain information and shape public opinion thus they are arenas of continuous competition for popularity. Most popular topics are usually indicated on ranking lists. In this study, we investigate the public attention dynamics through the Hot Search List (HSL) of the Chinese microblog Sina Weibo, where trending hashtags are ranked based on a multi-dimensional search volume index. We characterize the rank dynamics by the time spent by hashtags on the list, the time of the day they appear there, the rank diversity, and by the ranking trajectories. We show how the circadian rhythm affects the popularity of hashtags, and observe categories of their rank trajectories by a machine learning clustering algorithm. By analyzing patterns of ranking dynamics using various measures, we identify anomalies that are likely to result from the platform provider's intervention into the ranking, including the anchoring of hashtags to certain ranks on the HSL. We propose a simple model of ranking that explains the mechanism of this anchoring effect. We found an over-representation of hashtags related to international politics at 3 out of 4 anchoring ranks on the HSL, indicating possible manipulations of public opinion. |
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AbstractList | Microblogging sites are important vehicles for the users to obtain information and shape public opinion thus they are arenas of continuous competition for popularity. Most popular topics are usually indicated on ranking lists. In this study, we investigate the public attention dynamics through the Hot Search List (HSL) of the Chinese microblog Sina Weibo, where trending hashtags are ranked based on a multi-dimensional search volume index. We characterize the rank dynamics by the time spent by hashtags on the list, the time of the day they appear there, the rank diversity, and by the ranking trajectories. We show how the circadian rhythm affects the popularity of hashtags, and observe categories of their rank trajectories by a machine learning clustering algorithm. By analyzing patterns of ranking dynamics using various measures, we identify anomalies that are likely to result from the platform provider’s intervention into the ranking, including the anchoring of hashtags to certain ranks on the HSL. We propose a simple model of ranking that explains the mechanism of this anchoring effect. We found an over-representation of hashtags related to international politics at 3 out of 4 anchoring ranks on the HSL, indicating possible manipulations of public opinion. |
Audience | Academic |
Author | Kertész, János Cui, Hao |
AuthorAffiliation | University of Edinburgh, UNITED KINGDOM Department of Network and Data Science, Central European University, Vienna, Austria |
AuthorAffiliation_xml | – name: Department of Network and Data Science, Central European University, Vienna, Austria – name: University of Edinburgh, UNITED KINGDOM |
Author_xml | – sequence: 1 givenname: Hao surname: Cui fullname: Cui, Hao organization: Department of Network and Data Science, Central European University, Vienna, Austria – sequence: 2 givenname: János orcidid: 0000-0003-4957-5406 surname: Kertész fullname: Kertész, János organization: Department of Network and Data Science, Central European University, Vienna, Austria |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37220108$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1089/cyber.2017.0142 10.3389/fphy.2018.00045 10.1145/1935826.1935863 10.1016/j.physa.2023.128724 10.1109/TSMC.2018.2855806 10.1002/9781118575574 10.1109/CBD.2015.14 10.1007/978-3-540-74048-3_4 10.2139/ssrn.1888779 10.1609/icwsm.v5i1.14167 10.1016/j.tele.2016.05.022 10.1140/epjds/s13688-021-00263-0 10.1073/pnas.0704916104 10.1177/0002764215580619 10.1109/ICDM.2010.22 10.1371/journal.pone.0110184 10.1140/epjds/s13688-016-0096-y 10.1371/journal.pone.0131184 10.1080/19331681.2017.1308289 10.1109/ICWR.2019.8765252 10.1109/SocialCom.2013.58 10.1145/2512938.2512940 10.1038/s41467-022-29256-x 10.1007/s10878-013-9674-0 10.5210/fm.v17i3.3943 |
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Copyright | Copyright: © 2023 Cui, Kertész. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2023 Public Library of Science 2023 Cui, Kertész. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2023 Cui, Kertész 2023 Cui, Kertész 2023 Cui, Kertész. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist. Current address: Geary Institute for Public Policy, University College Dublin, Dublin, Ireland Current address: School of Sociology, University College Dublin, Dublin, Ireland |
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SubjectTerms | Algorithms Analysis Anomalies Biology and Life Sciences Blogging Celebrities China Circadian Rhythm Circadian rhythms Cluster Analysis Clustering Competition Computer and Information Sciences Coronaviruses COVID-19 Disease transmission Evaluation Evolution Humans Information management Machine learning Microblogs Pandemics Public health administration Public opinion Ranking Social networks Social Sciences Tagging Tags Trends |
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Title | Competition for popularity and interventions on a Chinese microblogging site |
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