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KDD_FULL_PRESENTATION.pdf

_themessier
August 25, 2020
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 KDD_FULL_PRESENTATION.pdf

_themessier

August 25, 2020
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  1. Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity

    Prediction Subhabrata Dutta 1, Sarah Masud 2, Soumen Chakrabarti 3, Tanmoy Chakraborty 2 1 Jadavpur University, India; 2 IIIT-Delhi, India; 3 IIT Bombay, India ACM SIGKDD 2020 August 23-27 Virtual Conference
  2. • Chatter intensity Research Motivation - how much people will

    talk, given a content - need to detect as early as possible - may help containing spread of malicious contents
  3. • Chatter intensity • Exogenous influence Research Motivation Season arrivals

    Discovery Detection Fig.1 Submissions and comments containing two different keywords on Reddit
  4. • Chatter intensity • External influence • Endogenous influence Research

    Motivation Fig.1 Submissions and comments containing ‘Black Mirror’ on different subreddits
  5. Research Motivation • Chatter intensity • External influence • Existing

    prediction frameworks Data Available Publicly • Discussion threads • Subreddit mapping • Who follows whom
  6. Unified Chatter Model • News, submissions and comments come in

    bulk and continuously, so Online prediction • Zero-shot or few-shot prediction • No social network is visible, rely on exogenous and endogenous signals
  7. Unified Chatter Model • News, submissions and comments come in

    bulk and continuously, so Online prediction • Zero-shot or few-shot prediction • No social network is visible, rely on exogenous and endogenous signals
  8. Unified Chatter Model • News, submissions and comments come in

    bulk and continuously, so Online prediction • Zero-shot or few-shot prediction • No social network is visible, rely on exogenous and endogenous signals
  9. Unified Chatter Model • News, submissions and comments come in

    bulk and continuously, so Online prediction • Zero-shot or few-shot prediction • No social network is visible, rely on exogenous and endogenous signals All in one! We propose ChatterNet!
  10. Dataset OCT 1, 2019 OCT 31, 2019 NOV 30, 2019

    Submission: 751,866 Comments: 2,604,839 Submission: 1,334,341 Comments: 4,264,177 Articles: 1,851,022 Sources: 4,757 Articles: 2,010,985 Sources: 5054 43 subreddits Training data Testing data
  11. ChatterNet: Main results + and ++ refers to zero-shot and

    1hr early observations, respectively
  12. Details of our framework at: github.com/LCS2-IIITD/ChatterNet For more interesting research

    follow us at: @lcs2iiitd ACM SIGKDD 2020 August 23-27 Virtual Conference