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Current Result Document :
ÇѱÛÁ¦¸ñ(Korean Title) |
Æ®À§ÅÍ ÀÌ°í-³×Æ®¿öÅ©¿¡¼ »ç¿ëÀÚ Ä£¹Ð¼º°ú °ü½É»ç À¯»çµµÀÇ »ó°ü°ü°è ºÐ¼® |
¿µ¹®Á¦¸ñ(English Title) |
Analysis on Correlation between User Affinity Features and Interest Similarity in Twitter Ego-Networks |
ÀúÀÚ(Author) |
¹Úâ¿í
Chang-Uk Park
È«Áö¿ø
Ji-Won Hong
±è»ó¿í
Sang-Wook Kim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 31 NO. 03 PP. 0049 ~ 0058 (2015. 12) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English Abstract) |
With Internet¡¯s development and its propagation, a massive amount of information is generated by Internet users. As such, there is a growing demand for personalized services that serve targeted information to each corresponding individual. Among many, one of the best examples of this growing need is Twitter social network service. Twitter users display their personal interests in various ways by posting and updating status to their timeline, and by showing their preferences on other people¡¯s tweets through ¡°retweet¡± or ¡°favorite¡± function. Recently, there have been many trials to offer Twitter users the personalized services based on Twitter social network analysis result. In general, personalized services utilize information of those the target user¡¯s nearest neighbors had been interested in. If it is available for utilizing useful additional information regarding to nearest neighbors, we can expect to provide services of better quality to users. Through this research, we study the correlation between user affinity features and users¡¯ interest similarity in social network. Then, we verify the expected utility of user affinity features in personalized services.
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Å°¿öµå(Keyword) |
¼Ò¼È ³×Æ®¿öÅ© ºÐ¼®
Æ®À§ÅÍ
ÀÌ°í-³×Æ®¿öÅ©
»ç¿ëÀÚ Ä£¹Ð¼º
°ü½É»ç À¯»çµµ
Social network analysis
Twitter
ego-network
user affinity
interest similarity
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