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Deception Detection in Online Media

Author

Listed:
  • Zaynutdinova, Alsu
  • Pisarevskaya, Dina
  • Zubov, Maxim
  • Makarov, Ilya

Abstract

Russian Federation and European Union are fighting againstfake news together with other countries in various topics. The disinform-ation affected British referendum of existing EU, the US election andCatalonia’s referendum are broadly studied. A need for automated fact-checking increases, European Commission’s Action Plan 8 is an evidence.In this work, we develop a model for detecting disinformation in Russianlanguage in online media. We use reliable and unreliable sources to com-pare named entities and verbs extracted using DeepPavlov library. Ourmethod shows four time greater recall compared to chosen baseline.

Suggested Citation

  • Zaynutdinova, Alsu & Pisarevskaya, Dina & Zubov, Maxim & Makarov, Ilya, 2019. "Deception Detection in Online Media," MPRA Paper 97316, University Library of Munich, Germany, revised 23 Sep 2019.
    • Handle: RePEc:pra:mprapa:97316
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    File URL: https://mpra.ub.uni-muenchen.de/97316/1/project5.pdf
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    More about this item

    Keywords

    Fake news; Information extraction; Fact checking; Deep-Pavlov; Named Entities;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • M38 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Government Policy and Regulation
    • Z18 - Other Special Topics - - Cultural Economics - - - Public Policy

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