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Real-World Witness Detection in Social Media via Hybrid Crowdsensing

Authors

Stefano Cresci,Andrea Cimino,Marco Avvenuti,Maurizio Tesconi,Felice Dell'Orletta

Institute of Informatics and Telematics-CNR,Institute of Computational Linguistics-CNR,University of Pisa,Institute of Informatics and Telematics-CNR,Institute of Computational Linguistics-CNR


Proceedings:

Vol. 12 No. 1 (2018): Twelfth International AAAI Conference on Web and Social Media

Volume

Issue:

Vol. 12 No. 1 (2018): Twelfth International AAAI Conference on Web and Social Media

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Poster Papers

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Abstract:

The task of witness detection in social media is crucial for many practical applications, including rumor debunking, emergency management, and public opinion mining. Yet to date, it has been approached in an approximated way. We propose a method for addressing witness detection in a strict and realistic fashion. By employing hybrid crowdsensing over Twitter, we contact real-life witnesses and use their reactions to build a strong ground-truth, thus avoiding a manual, subjective annotation of the dataset. Using this dataset, we develop a witness detection system based on a machine learning classifier using a wide set of linguistic features and metadata associated with the tweets.

DOI:

10.1609/icwsm.v12i1.15072


ICWSM

Vol. 12 No. 1 (2018): Twelfth International AAAI Conference on Web and Social Media