Extracting and Aggregating False Information from Microblogs
نویسندگان
چکیده
During the 2011 East Japan Earthquake and Tsunami Disaster, we had found a number of false information spread on Twitter, e.g., “The Cosmo Oil explosion causes toxic rain.” This paper extracts pieces of false information exhaustively from all the tweets within one week after the earthquake. Designing a set of linguistic patterns that correct false information, this paper proposes a method for detecting false information. More specifically, the method extracts text passages that match to the correction patterns, clusters the passages into topics of false information, and selects, for each topic, a passage explaining the false information the most suitably. In the experiment, we report the performance of the proposed method on the data set extracted manually from Web sites that are specialized in collecting false information.
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