Proceedings of the 2014 International Conference on Computer, Communications and Information Technology

Detection of Internet Water Army in Social Network

Authors
Kun Wang, Yang Xiao, Zhen Xiao
Corresponding Author
Kun Wang
Available Online January 2014.
DOI
10.2991/ccit-14.2014.50How to use a DOI?
Keywords
Internet Water Army, Feature measurement, Machine learning, Influence model, MEIWA online algorithm
Abstract

As related works had a few research on Internet Water Army in social network, specifically on the Internet Water Army who trends to lead people’s opinions, obscure the real voices and change public opinions in social network. To better understand what difference lie between Internet Water Army and legitimate user, we did some work about behaviour of them from real dataset in Sina microblogging service. We adopted some machine learning algorithms to classify the type of user with collected features through the measurement. At the same time we proposed an influence model and create a new online algorithm with linear complexity to reduce the water army’s influence on legitimate users greatly.

Copyright
© 2014, 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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Volume Title
Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
Series
Advances in Intelligent Systems Research
Publication Date
January 2014
ISBN
978-90786-77-97-0
ISSN
1951-6851
DOI
10.2991/ccit-14.2014.50How to use a DOI?
Copyright
© 2014, 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/).

Cite this article

TY  - CONF
AU  - Kun Wang
AU  - Yang Xiao
AU  - Zhen Xiao
PY  - 2014/01
DA  - 2014/01
TI  - Detection of Internet Water Army in Social Network
BT  - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
PB  - Atlantis Press
SP  - 189
EP  - 192
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.50
DO  - 10.2991/ccit-14.2014.50
ID  - Wang2014/01
ER  -