The Weibo Spammers’ Identification and Detection based on Bayesian-algorithm

DOI

10.2991/wartia-16.2016.271How to use a DOI?

Keywords

Weibo, spammer, identification and detection, Bayesian-algorithm, Genetic-algorithm,

Abstract

The Weibo spammers are employed in latent network public relations or marketing companies, whose job is to achieve publicity or vilify the effect by means of organizing and planning the focus of speculation to a topic or person. In order to reduce the bad influence caused by them, this paper intends to establish a classifier based on the behavior characteristics. By analyzing the previous research, we set the ratio of followers, total number of blog posts, the number of friends, comprehensive quality evaluation and favorates according to latest data. Based on Bayesianalgorithm and Geneticalgorithm, we use R and Matlab to determine the optimal threshold matrix and conditional probability matrix of the changeable Weibo spammers. After testing, it has higher recognition accuracy.

Copyright

© 2016, 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  - Yingying Huang
AU  - Mengyi Zhang
AU  - Yuqing Yang
AU  - Shijie Gan
AU  - Yanmei Zhang
PY  - 2016/05
DA  - 2016/05
TI  - The Weibo Spammers’ Identification and Detection based on Bayesian-algorithm
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1291
EP  - 1297
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.271
DO  - 10.2991/wartia-16.2016.271
ID  - Huang2016/05
ER  -