Exploring the COVID-19 Vaccine-related Opinion Shifting of Users on Twitter

Sun, Ran; An, Lu

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https://hdl.handle.net/2142/122818 Copy

Description

Title

Exploring the COVID-19 Vaccine-related Opinion Shifting of Users on Twitter

Author(s)

• Sun, Ran
• An, Lu

Issue Date

2024-03-20

Keyword(s)

• Opinion shifting
• Topic analysis
• Sentiment analysis
• Social media
• Vaccine

Abstract

Understanding public opinion on social media is vital for developing evidence-based interventions that drive positive change in global Covid-19 vaccination efforts. This ongoing study thus addresses the public opinion shifting on Twitter through the analysis of over 200k users engaged in online discussions related to the Covid-19 vaccine. We then operationalize opinion shifting in three dimensions: word 1-grams shifting, topic shifting and sentiment shifting. Day-scale usage frequency distributions for 1-grams are compared by rank turbulence divergence and the Mann-Kendall Mutation analysis is applied to determine the discussion shift based on the divergence score per two days. Text analysis methods are employed for topic clustering and sentiment analysis on tweets. Based on analyzing users' topic shifting, we explore opinion shifting from their sentiment changes on a topic. Our findings indicate that more than half of the social media users experience vaccine-related topic shifting. Users who experience topic shifting and who focus on a single topic have slightly different patterns of sentiment shifting when they hold the same sentiment on a topic. Individuals who focus on a single topic tend to experience increased sentiment polarization toward a particular sentiment direction over time.

Publisher

iSchools

Series/Report Name or Number

iConference 2024 Proceedings

Type of Resource

Other

Language

eng

Handle URL

https://hdl.handle.net/2142/122818

Copyright and License Information

Copyright 2024 is held by Ran Sun and Lu An. Copyright permissions, when appropriate, must be obtained directly from the authors.

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