Temporal provenance discovery in micro-blog message streams (abstract only)
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Recent years have witnessed the flourishing increases of micro-blog message applications. Prominent examples include Twitter, Facebook's status, and Sina Weibo in China. Messages in these applications are short (140 characters in a message) and easy to create. The subscription and re-sharing features also make it fairly intuitive to propagate. Micro-blog applications provide abundant information to present world scale user interests and social pulse in an unexpected way. But the precious corpus also brings out the noise and fast changing fragments to prohibit effective understanding and management. In this work, we propose a micro-blog provenance model to capture temporal connections within micro-blog messages.
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