Abstract
This study investigates the influences of the prosocial and antisocial tendency of Weibo users on post transmission during the COVID-19 pandemic. To overcome the deficiency of existing research on prosocial and antisocial emotions, we employ a web crawler technology to obtain post data from Weibo and identify texts with prosocial or antisocial emotions. We use SnowNLP to construct semantic dictionaries and training models. Our major findings include the following. First, through correlation analysis and negative binomial regression, we find that user posts with high intensity and prosocial emotion can trigger comments or forwarding behaviour. Second, the influence of antisocial emotion on Weibo comments, likes, and retweets are insignificant. Third, the general emotion about prosocial comments in Weibo also shows the emotion trend of prosocial comments. Overall, a major contribution of this paper is our focus on prosocial and antisocial emotions in cyberspace, providing a new perspective on emotion communication.
Highlights
Since the outbreak of the new coronavirus in late 2019, more than 200 countries and billions of people worldwide have been severely impacted
Online antisocial behaviour has begun to become widespread and persistent with the widespread use of online social media in recent years. is behaviour was once called cyberbullying in 2000, but it is referred to as cyber “sprays.” In Weibo discussions on the pandemic, we anticipate encouragement and comfort but cannot ignore hatred and abuse. e spread of pro-(anti-) social emotions affects our experience in the Weibo community and relates to how we get through the crisis
To control the experimental errors in these aspects, this study uses a web crawler to collect user data from the real Weibo environment. It uses natural language processing (SnowNLP) to automatically score emotion tendencies and avoid the subjective effects of artificial coding to ensure the objectivity of the study. is research is closely related to the discussion of the epidemic event of COVID-19 and through this major public crisis to explore the common prosocial phenomenon in cyberspace. rough exploring the role of prosocial emotion in Weibo information transmission and arousing the attention of online users from all walks of life to be aware of this antisocial phenomenon, the creation of a more directed online environment can actively encourage the expression of prosocial emotion. is is a major contribution of this research
Summary
Since the outbreak of the new coronavirus in late 2019, more than 200 countries and billions of people worldwide have been severely impacted. According to its first quarter earnings data, active users were 550 million per month, including 241 million users who used frequently Social media, such as Weibo, provide freedom and convenience for online discussion and become an outlet for public catharsis. Prosocial and antisocial behaviours are a topic worthy of attention in offline society and have important research value in online social networks. Rough exploring the role of prosocial emotion in Weibo information transmission and arousing the attention of online users from all walks of life to be aware of this antisocial phenomenon, the creation of a more directed online environment can actively encourage the expression of prosocial emotion. It uses natural language processing (SnowNLP) to automatically score emotion tendencies and avoid the subjective effects of artificial coding to ensure the objectivity of the study. is research is closely related to the discussion of the epidemic event of COVID-19 and through this major public crisis to explore the common prosocial phenomenon in cyberspace. rough exploring the role of prosocial emotion in Weibo information transmission and arousing the attention of online users from all walks of life to be aware of this antisocial phenomenon, the creation of a more directed online environment can actively encourage the expression of prosocial emotion. is is a major contribution of this research
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
