Analysis of Behavior Patterns to Identify Nicknames of a User in Online Community

  title={Analysis of Behavior Patterns to Identify Nicknames of a User in Online Community},
  author={Sang-Hyun Park and So-Hye Yoon and Juwon Jeong and Sehwa Park and Seog Park},
  journal={2018 IEEE International Conference on Big Data and Smart Computing (BigComp)},
An online community is a virtual group that is mediated through the Internet for users to share interests and hobbies. Unlike social network service (SNS), an online community is an anonymous service mainly based on nickname. Some users exploit this anonymity and conduct malicious activities. Actions should be taken to filter these users and limit their activities. One problem lies in that nicknames are frequently changed in online communities, and automatically filtering nicknames is difficult… CONTINUE READING

Similar Papers

Figures, Tables, Results, and Topics from this paper.

Key Quantitative Results

  • Among the machine learning algorithms, the random forest showed the best performance, and the nickname of the same user was identified with an accuracy of about 92.9%.
  • Experimental result on the usage pattern showed accuracy of 84.4% when using random forest, which indicates that numerical information generated by posts and comments reveals user’s unique characteristics.


Publications referenced by this paper.

2015 Survey of the Internet Usage

Korea Internet, Security Agency
  • pp.65-66, 2015.(in Korean)
  • 2015

Big Data Privacy Risk Analysis

Daeseon Choi, Seok Hyun Kim, Jin-Man Cho, Seung-Hun Jin
  • Review of KISSC, Vol.13,
  • 2013

Comparison of Social Relationship Formation Mechanism between SNS and Online Community

Korea Information Society Development Institute
  • pp.70-72, 2012.(in Korean)
  • 2012

Studying User Footprints in Different Online Social Networks

  • 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
  • 2012