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Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat
We analyze a Singapore-based COVID-19 Telegram group with more than 10000 participants. First, we study the group’s opinion over time, focusing on five dimensions: participation, sentiment, negative emotions, topics, and message types. We find that participation peaked when the Ministry of Health ra...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
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IEEE
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280806/ https://www.ncbi.nlm.nih.gov/pubmed/35938074 http://dx.doi.org/10.1109/MIC.2020.3040516 |
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collection | PubMed |
description | We analyze a Singapore-based COVID-19 Telegram group with more than 10000 participants. First, we study the group’s opinion over time, focusing on five dimensions: participation, sentiment, negative emotions, topics, and message types. We find that participation peaked when the Ministry of Health raised the disease alert level, but this engagement was not sustained. Second, we investigate the prevalence of, and reactions to, authority-identified misinformation in the group. We find that authority-identified misinformation is rare, and that participants affirm, deny, and question misinformation. Third, we explore searching for user skepticism as one strategy for identifying misinformation, finding misinformation not previously identified by authorities. |
format | Online Article Text |
id | pubmed-9280806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | IEEE |
record_format | MEDLINE/PubMed |
spelling | pubmed-92808062022-08-01 Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat IEEE Internet Comput Theme Article: CYBER SOCIAL HEALTH We analyze a Singapore-based COVID-19 Telegram group with more than 10000 participants. First, we study the group’s opinion over time, focusing on five dimensions: participation, sentiment, negative emotions, topics, and message types. We find that participation peaked when the Ministry of Health raised the disease alert level, but this engagement was not sustained. Second, we investigate the prevalence of, and reactions to, authority-identified misinformation in the group. We find that authority-identified misinformation is rare, and that participants affirm, deny, and question misinformation. Third, we explore searching for user skepticism as one strategy for identifying misinformation, finding misinformation not previously identified by authorities. IEEE 2020-12-11 /pmc/articles/PMC9280806/ /pubmed/35938074 http://dx.doi.org/10.1109/MIC.2020.3040516 Text en This article is free to access and download, along with rights for full text and data mining, re-use and analysis. |
spellingShingle | Theme Article: CYBER SOCIAL HEALTH Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title | Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title_full | Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title_fullStr | Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title_full_unstemmed | Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title_short | Analyzing Public Opinion and Misinformation in a COVID-19 Telegram Group Chat |
title_sort | analyzing public opinion and misinformation in a covid-19 telegram group chat |
topic | Theme Article: CYBER SOCIAL HEALTH |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9280806/ https://www.ncbi.nlm.nih.gov/pubmed/35938074 http://dx.doi.org/10.1109/MIC.2020.3040516 |
work_keys_str_mv | AT analyzingpublicopinionandmisinformationinacovid19telegramgroupchat AT analyzingpublicopinionandmisinformationinacovid19telegramgroupchat |