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
ISSN2329-924X
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
DOI10.1109/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
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被引频次:4[WOS]   [WOS记录]     [WOS相关记录]
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.
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