@inproceedings{16c47428961d488b96d1cfaf69b3bf12,
title = "A graph-based reliable user classification",
abstract = "When some hot social issue or event occurs, it will significantly increase the number of comments and retweet on that day on Twitter. However, as the amount of SNS data increases, the noise also increases synchronously, thus a reliable user classification method is being required. In this paper, we classify the users who are interested in the issue as {"}socially well-known user{"} and {"}reliable and highly active user{"}. {"}A graph-based user reliability measurement{"} and {"}Weekly user activity measurement{"} are introduced to classify users who are interested in the issue. Eight of social issues were experimented in Twitter data to verify validity of the proposed method. The top 10 results of the experiment showed 76.8\% of performance in average precision (P@10). The experimental results show that the proposed method is effective for classifying users in Twitter corpus.",
keywords = "Graph-based user metric, Timeline analysis, User classification",
author = "Bayar Tsolmon and Lee, \{Kyung Soon\}",
year = "2014",
doi = "10.1007/978-981-4585-18-7\_7",
language = "English",
isbn = "9789814585170",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "61--68",
booktitle = "Proceedings of the First International Conference on Advanced Data and Information Engineering, DaEng 2013",
note = "1st International Conference on Advanced Data and Information Engineering, DaEng 2013 ; Conference date: 16-12-2013 Through 18-12-2013",
}