Privacy-preserving discovery of topic-based events from social sensor signals: an experimental study on Twitter

基于社交传感器信号,在保护隐私的前提下发现主题事件:一项关于 Twitter 的实验研究

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Abstract

Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.

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