COVID-19 on Social Media: Analyzing Misinformation in Twitter
Conversations
- URL: http://arxiv.org/abs/2003.12309v4
- Date: Thu, 22 Oct 2020 03:03:29 GMT
- Title: COVID-19 on Social Media: Analyzing Misinformation in Twitter
Conversations
- Authors: Karishma Sharma, Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan
Liu
- Abstract summary: We collected streaming data related to COVID-19 using the Twitter API, starting March 1, 2020.
We identified unreliable and misleading contents based on fact-checking sources.
We examined the narratives promoted in misinformation tweets, along with the distribution of engagements with these tweets.
- Score: 22.43295864610142
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The ongoing Coronavirus (COVID-19) pandemic highlights the
inter-connectedness of our present-day globalized world. With social distancing
policies in place, virtual communication has become an important source of
(mis)information. As increasing number of people rely on social media platforms
for news, identifying misinformation and uncovering the nature of online
discourse around COVID-19 has emerged as a critical task. To this end, we
collected streaming data related to COVID-19 using the Twitter API, starting
March 1, 2020. We identified unreliable and misleading contents based on
fact-checking sources, and examined the narratives promoted in misinformation
tweets, along with the distribution of engagements with these tweets. In
addition, we provide examples of the spreading patterns of prominent
misinformation tweets. The analysis is presented and updated on a publically
accessible dashboard (https://usc-melady.github.io/COVID-19-Tweet-Analysis) to
track the nature of online discourse and misinformation about COVID-19 on
Twitter from March 1 - June 5, 2020. The dashboard provides a daily list of
identified misinformation tweets, along with topics, sentiments, and emerging
trends in the COVID-19 Twitter discourse. The dashboard is provided to improve
visibility into the nature and quality of information shared online, and
provide real-time access to insights and information extracted from the
dataset.
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