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

机译:分析行为模式以识别在线社区中用户的昵称

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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 when they are constantly malicious. Another problem is data fragmentation in which the data of the same user exists under different nicknames due to the first problem. Therefore, to solve these issues, we propose a behavior pattern feature vector, which considers online community characteristics and identifies nicknames of the same user. Specifically, we propose a method to identify nicknames of the same user using actual data of an online community in Korea.
机译:在线社区是一个虚拟团体,通过互联网进行调解,以使用户共享兴趣和爱好。与社交网络服务(SNS)不同,在线社区是主要基于昵称的匿名服务。一些用户利用这种匿名性进行恶意活动。应该采取措施过滤这些用户并限制其活动。一个问题在于,昵称在在线社区中经常更改,并且当它们不断受到恶意攻击时,很难自动过滤昵称。另一个问题是数据碎片,其中由于第一个问题,同一用户的数据以不同的昵称存在。因此,为了解决这些问题,我们提出了一种行为模式特征向量,该向量考虑了在线社区特征并标识了同一用户的昵称。具体而言,我们提出一种使用韩国在线社区的实际数据来识别同一用户的昵称的方法。

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