Detecting Spam on Sina Weibo

DOI

10.2991/ccis-13.2013.93How to use a DOI?

Keywords

Spam Detection; Social Network Security; Machine Learning

Abstract

Online social network becomes greatly prevalent and evolves a communication channel for billions of users. Unfortunately, due to the ease of reaching these users, it has been penetrated by spammers who post inappropriate content. After revealing the transmission mechanism of the spam, an automatic detecting framework is designed to identify spam information. The profiles which have multiple discriminative features are extracted for the Machine Learning techniques. In the experiment phase we collected 562K messages posted by 28,679 users on Sina Weibo, then analyzed the different behaviors between malicious accounts and normal ones. We evaluate our approach on a real large-scale dataset. The results demonstrate the effectiveness of the detecting system.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ma Yingcai
AU  - Niu Yan
AU  - Ren Yan
AU  - Xue Yibo
PY  - 2013/11
DA  - 2013/11
TI  - Detecting Spam on Sina Weibo
BT  - Proceedings of the The 1st International Workshop on Cloud Computing and Information Security
PB  - Atlantis Press
SP  - 404
EP  - 407
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccis-13.2013.93
DO  - 10.2991/ccis-13.2013.93
ID  - Yingcai2013/11
ER  -