Dissecting emotion and user influence in social media communities: An interaction modeling approach
文献类型：期刊论文
| 作者 | Chung, Wingyan2; Zeng, Daniel1,3
|
| 刊名 | INFORMATION & MANAGEMENT
 |
| 出版日期 | 2020 |
| 卷号 | 57期号:1页码:16 |
| 关键词 | Emotion Network analysis Sentiment analysis Social media analytics Emotion extraction Influence modeling Causal modeling Social computing Border security |
| ISSN号 | 0378-7206 |
| DOI | 10.1016/j.im.2018.09.008 |
| 通讯作者 | Chung, Wingyan(wchung@ucf.edu) |
| 英文摘要 | Human emotion expressed in social media plays an increasingly important role in shaping policies and decisions. However, the process by which emotion produces influence in online social media networks is relatively unknown. Previous works focus largely on sentiment classification and polarity identification but do not adequately consider the way emotion affects user influence. This research developed a novel framework, a theory-based model, and a proof-of-concept system for dissecting emotion and user influence in social media networks. The system models emotion-triggered influence and facilitates analysis of emotion-influence causality in the context of U.S. border security (using 5,327,813 tweets posted by 1,303,477 users). Motivated by a theory of emotion spread, the model was integrated in an influence-computation method, called the interaction modeling (IM) approach, which was compared with a benchmark using a user centrality (UC) approach based on social positions. IM was found to have identified influential users who are more broadly related to U.S. cultural issues. Influential users tended to express intense emotions of fear, anger, disgust, and sadness. The emotion trust distinguishes influential users from others, whereas anger and fear contributed significantly to causing user influence. The research contributes to incorporating human emotion into the data-information-knowledge-wisdom model of knowledge management and to providing new information systems artifacts and new causality findings for emotion-influence analysis. |
| WOS关键词 | BUSINESS INTELLIGENCE ; DECISION-MAKING ; SENTIMENT ; DIFFUSION ; ANALYTICS ; FRAMEWORK ; NETWORKS |
| 资助项目 | U.S. Defense Advanced Research Projects Agency[FA8650-18-C-7824] ; Florida Center for Cybersecurity[2108-1106-00-G] ; National Natural Science Foundation of China[71621002] ; Chinese Academy of Sciences[ZDRW-XH-2017-3] |
| WOS研究方向 | Computer Science ; Information Science & Library Science ; Business & Economics |
| 语种 | 英语 |
| WOS记录号 | WOS:000513292200009 |
| 出版者 | ELSEVIER |
| 资助机构 | U.S. Defense Advanced Research Projects Agency ; Florida Center for Cybersecurity ; National Natural Science Foundation of China ; Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/38505]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心 |
| 通讯作者 | Chung, Wingyan |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Cent Florida, Inst Simulat & Training, 3100 Technol Pkwy, Orlando, FL 32826 USA 3.Univ Arizona, Eller Coll Management, Dept Management Informat Syst, 1130 E Helen St, Tucson, AZ 85721 USA |
| 推荐引用方式 GB/T 7714 | Chung, Wingyan,Zeng, Daniel. Dissecting emotion and user influence in social media communities: An interaction modeling approach[J]. INFORMATION & MANAGEMENT,2020,57(1):16. |
| APA | Chung, Wingyan,&Zeng, Daniel.(2020).Dissecting emotion and user influence in social media communities: An interaction modeling approach.INFORMATION & MANAGEMENT,57(1),16. |
| MLA | Chung, Wingyan,et al."Dissecting emotion and user influence in social media communities: An interaction modeling approach".INFORMATION & MANAGEMENT 57.1(2020):16. |
入库方式： OAI收割
来源：自动化研究所
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