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논문 기본 정보

자료유형
학술대회자료
저자정보
Insoo Son (Korea University) Esther Kim (Korea University) Dongwon Lee (Korea University)
저널정보
한국지능정보시스템학회 한국지능정보시스템학회 학술대회논문집 한국지능정보시스템학회 2012년 추계학술대회
발행연도
2012.12
수록면
55 - 62 (8page)

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초록· 키워드

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Micro-blogging has been rapidly growing and gaining explosive popularity worldwide. Among the multiple micro-blogging services available in the market, Twitter is the most popular one so far. In particular, the service is characterized with “Retweet” feature, which represents how a user’s or a groups’ ideas are disseminated throughout an online communication environment. In this study, we explore the information diffusion mechanism under online social network environments by investigating the effect of message and user characteristics on multiple dimensions of Retweet phenomenon including volume, speed, and duration. We collected about 11k tweet messages related to the subjects of major telecom service providers in Korea (i.e., SK, KT, and LGU Plus) between September 2011 and December 2011. These original tweet messages have been retweeted at least once and generated more than 59k retweets. For the empirical test, we identified contextual factors derived from message and user characteristics and conducted multiple regression analysis. We found that information features inherent in tweet messages, such as URL, Hashtag and message length, have significant effect on retweet volume and duration. Our results also show that the retweet volume is affected by message content. The findings in the study suggest that some user characteristics, such as user identity, social relation with other users, and the level of tweet participation, have strong relationship with the speed and duration of retweet. From academic perspective, our study broadens theoretical knowledge of information diffusion mechanism over online social media. For practitioners, the study also provides managerial implications regarding how to strategically utilize online social media for marketing communications with customers.

목차

Abstract
Introduction
Literature Review
Data
Research Model
Analysis Results
Discussion
Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2014-003-000361471