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Filtering Twitter
Filtering Twitter
Filtering Twitter
Filtering Twitter
Filtering Twitter
Filtering Twitter
Filtering Twitter
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Filtering Twitter

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  • 1. Twitter is noisy but you can find some diamonds
  • 2. Pew Internet report: “75% of online news consumers say they get news forwarded through email or posts on social networking sites and 52% say they share links to news with others via those means.”
  • 3. Twitter Lists • Filtering main friends timeline is a bad idea • Twitter Lists: manually created set of users who often post on a certain topic • For example: – @huffingtonpost/apple-news – @IndieFlix/film-people-to-follow – @alisohani/bigdata-analytics • A Twitter user can be included into different lists. • Me for example: http://twitter.com/mariagrineva/lists/memberships
  • 4. What kind of noise? • People tweet on other topics too, including personal stuff • Global news widely spread, often really annoying: IPad launch, ash clouds, Christmas, Michael Jackson
  • 5. Our Approach • Identifying niche topic of Twitter list automatically, at real-time • Improve the niche topic with respect to the Global Twitter Stream – If there is a burst related to Apple, IPad => check maybe all Twitter is talking about that
  • 6. Filtering = Classification • Traditional approaches to filter news use only textual features • We use both textual and social features for classification – Twitter lists is a community of interconnected users => see who is the center and who is an outsider
  • 7. What is done • Method for identification list’s topic signature with respect to Global Twitter Stream • Social features identification • Evaluation framework

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