Papers by Akira Sasaki

    1 papers
    Predicting Stances from Social Media Posts using Factorization Machines (C18-1)

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    Challenge: Social media provide platforms to express, discuss, and shape opinions about events and issues in the real world.
    Approach: They propose to use factorization machines to model user preferences toward topics from social media data to predict whether a given text/user is in favor (agree), against (disagreer), or neutral toward a target topic.
    Outcome: The proposed method can predict stances of silent users based on their stance toward other topics and the social media posts of the user.

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