Competition or coexistence: Diffusion network differences between entertainment events and public events on social media

被引:0
作者
Su, Sini [1 ]
Dai, Yusong [1 ]
Xu, Xiaoke [2 ]
Zhong, Zhijin [1 ]
机构
[1] Sun Yat Sen Univ, Sch Journalism & Commun, Guangzhou, Peoples R China
[2] Beijing Normal Univ, Sch Journalism & Commun, Beijing, Peoples R China
关键词
Diffusion network differences; Social media; Entertainment information; Public information; Computational method; NEWS; CHOICE; GAPS;
D O I
10.1016/j.ipm.2025.104087
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
There is a prevalent concern that public information will be marginalized due to the prevailing preference for entertainment content on social media, consequently impacting public engagement. Despite extensive discussions, the relationship between entertainment and public affairs remains ambiguous. Unlike the majority of relative studies that examine broad phenomena or topics, we focus on event-specific diffusion networks, thereby avoiding ambiguous information categorization. Specifically, we separately selected 10 of the most influential events that happened from 9:00 to 15:00 on June 23, 2021, in both entertainment and public fields on Weibo. The collected dataset comprises 4,361,793 original posts, 16,511,446 reposts, and 10,557,370 users. Based on the diffusion network of entertainment events with those of public events, we observed that entertainment events do not divert attention from public events closely associated with people's lives. This remains the case despite entertainment events steadily exhibiting higher diffusion characteristics than those of most public events. Notably, public events can sustain public attention and discussions for longer. In addition, there are differences between the early followers of public events and entertainment events. The former predominantly comprises unverified users, while the latter mainly consists of verified users. Overall, the flow of sentiment tends to be consistent, stable, and transferable in both types of events. This study also utilized event data from June to December 2020, which underwent a complete diffusion process, to reaffirm these findings, thereby validating their explanatory power on a larger scale.
引用
收藏
页数:20
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