Communications in Humanities Research ISSN: 2753-7072
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Research Article

Temporal Dynamics of Online Sentiments: Investigating the Impact of Real-World Events on #StopAsianHate Twitter Movement

Li'an RenXi'an Jiaotong University* Tianlin LiuDel Norte High School Junming ZhengChangwai Bilingual School Luyao ZhaoAffiliated High School of South China Normal University International Department Haobo ZhangHigh School Affiliated to Renmin University of China

* Corresponding author: [email protected]

Abstract

Stop Asian hate has been a heated topic on social media platforms because of the increase in Asian hate after the breakout of COVID-19 and hate crimes caused by Asian hate. The hashtag #StopAsianHate on Twitter points out that making proper consensus decisions can be an effective way to spread the impact of hate crimes and attract more attention to Asian hate to call for actions to stop Asian hate. To gain more theoretical knowledge for consensus decisions and guidance of public opinion, this study used MDCOR and tools developed by our researchers to analyze posts under tweets (opened answers) posted under the hashtag #StopAsianHate (from March 1, 2022, to August 31, 2023). The tools being used can directly analyze the open answers on Twitter, providing the study with the identification of topics and sentiment analysis. Through the analysis of 5-month data, which is far longer than other research, the dynamic of the public’s opinion and sentiment is clearly shown. By understanding the shifts in public opinion and sentiment, more valid strategies for advocacy of anti-racism are hoped to be found.

Keywords: Stop Asian Hate; Data Mining; Social Media; Sentiment Analysis
Published: May 17, 2024
DOI: 10.54254/2753-7064/31/20232009
Volume: CHR Vol.31
pp. 126-139
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  19. R code for the heat graph and association graph: https://drive.google.com/file/d/13DHWT7wJd3WHc71FITpwP4CY7D8R8OB4/view?usp=sharing https://drive.google.com/file/d/1-RSkMm9vFRtTK_xhgvalmN6B1d4Y8Jk-/view?usp=share_link