Knowledge Commons of Institute of Automation,CAS
Game Starts at GameStop: Characterizing the Collective Behaviors and Social Dynamics in the Short Squeeze Episode | |
Zheng, Xiaolong1,2; Tian, Hu1,2; Wan, Zhe3; Wang, Xiao1,2; Zeng, Daniel Dajun1,2; Wang, Fei-Yue1,2 | |
发表期刊 | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS |
ISSN | 2329-924X |
2021-11-08 | |
页码 | 14 |
摘要 | In January 2021, the users of subreddit r/wallstreetbets (WSB) triggered an unprecedented short squeeze by driving up GameStop's stock price to an unimaginable high point. During the event, a large number of users participated in the discussion about GameStop and coordinated trading behavior on r/WSB to push the stock price higher. In this article, we investigate the characteristics of the collective behaviors and social dynamics from the evolutions of topological structure, discussed topics, and user sentiment polarity (SP) by constructing dynamic interaction networks, modeling the topic, and analyzing the user sentiment. We find that the topological structure of the interaction network evolves toward a more efficient direction, the discussed topics change more centralized, and the user sentiment tends to be more positive and divergent. And we reveal that part of GameStop's stock price is explained by the social media activity, popularity of the dominant topic, topic cohesiveness, SP of users, and sentiment divergence between interacted users on r/WSB. Our work quantitatively characterizes the interaction networks and user behavior during the GameStop short squeeze and provides an example to analyze the event which synchronously evolves in the physical space and cyberspace. It not only contributes to the analysis of social system behavior and structure but also provides valuable insights into the financial practice and policy decision-making. |
关键词 | Social networking (online) Dictionaries Stock markets Investment Games Analytical models Market research Dynamic interaction network financial market GameStop short squeeze social network analysis |
DOI | 10.1109/TCSS.2021.3122260 |
关键词[WOS] | INVESTOR SENTIMENT ; MEDIA ; SPACE ; POWER |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Ministry of Science and Technology of China[2020AAA0108401] ; Natural Science Foundation of China[71602184] ; Natural Science Foundation of China[71621002] |
项目资助者 | Ministry of Science and Technology of China ; Natural Science Foundation of China |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Cybernetics ; Computer Science, Information Systems |
WOS记录号 | WOS:000732412900001 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 社会计算 |
国重实验室规划方向分类 | 社会系统建模与计算 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46885 |
专题 | 多模态人工智能系统全国重点实验室_平行智能技术与系统团队 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
通讯作者 | Wang, Fei-Yue |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 3.Beijing Normal Univ, Belt & Rd Sch, Beijing 100875, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zheng, Xiaolong,Tian, Hu,Wan, Zhe,et al. Game Starts at GameStop: Characterizing the Collective Behaviors and Social Dynamics in the Short Squeeze Episode[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2021:14. |
APA | Zheng, Xiaolong,Tian, Hu,Wan, Zhe,Wang, Xiao,Zeng, Daniel Dajun,&Wang, Fei-Yue.(2021).Game Starts at GameStop: Characterizing the Collective Behaviors and Social Dynamics in the Short Squeeze Episode.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,14. |
MLA | Zheng, Xiaolong,et al."Game Starts at GameStop: Characterizing the Collective Behaviors and Social Dynamics in the Short Squeeze Episode".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2021):14. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Game_Starts_at_GameS(8005KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 |
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