Contagion of Cheating Behaviors in Online Social Networks
DC Field | Value | Language |
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dc.contributor.author | Woo, Jiyoung | - |
dc.contributor.author | Kang, Sung Wook | - |
dc.contributor.author | Kim, Huy Kang | - |
dc.contributor.author | Park, Juyong | - |
dc.date.accessioned | 2021-09-02T21:17:40Z | - |
dc.date.available | 2021-09-02T21:17:40Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2018 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/80970 | - |
dc.description.abstract | Human behaviors are known to spread through social contact. The diffusion process on social networks has also been leveraged to understand the spread of undesirable contagion. The contagion of malicious or even criminal behaviors in online social networks is just beginning to attract attention. Here, we study the social contagion problem of cheating behavior found in the massively multiplayer online roleplaying game (MMORPG) that provides a lifelike environment with rich and realistic user interactions. Because cheating users boast an abnormal thus conspicuous degree of success, it has a strong chance of being noticed by their friends and leading them to cheat themselves. To detect and prevent cheating, it is beneficial to understand this dynamic as a contagion problem. In this paper, we show the existence of the contagion of cheating. We then explore various possible social reinforcement mechanisms after introducing several factors to quantify the effect of social reinforcement on the contagion and analyze the dynamics of bot diffusion in an extensive user interaction log from a major MMORPG. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | DIFFERENTIAL ASSOCIATION | - |
dc.subject | LEARNING THEORY | - |
dc.subject | COMPUTER CRIME | - |
dc.subject | SMOKING | - |
dc.subject | MODEL | - |
dc.subject | INFORMATION | - |
dc.subject | PERSPECTIVE | - |
dc.subject | CONFORMITY | - |
dc.subject | DIFFUSION | - |
dc.subject | DRINKING | - |
dc.title | Contagion of Cheating Behaviors in Online Social Networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Huy Kang | - |
dc.identifier.doi | 10.1109/ACCESS.2018.2834220 | - |
dc.identifier.scopusid | 2-s2.0-85046400220 | - |
dc.identifier.wosid | 000435521100011 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.6, pp.29098 - 29108 | - |
dc.relation.isPartOf | IEEE ACCESS | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 6 | - |
dc.citation.startPage | 29098 | - |
dc.citation.endPage | 29108 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | DIFFERENTIAL ASSOCIATION | - |
dc.subject.keywordPlus | LEARNING THEORY | - |
dc.subject.keywordPlus | COMPUTER CRIME | - |
dc.subject.keywordPlus | SMOKING | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | INFORMATION | - |
dc.subject.keywordPlus | PERSPECTIVE | - |
dc.subject.keywordPlus | CONFORMITY | - |
dc.subject.keywordPlus | DIFFUSION | - |
dc.subject.keywordPlus | DRINKING | - |
dc.subject.keywordAuthor | Diffusion model | - |
dc.subject.keywordAuthor | social contagion | - |
dc.subject.keywordAuthor | social network | - |
dc.subject.keywordAuthor | online game | - |
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