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Augmenting Stylometric Features to Improve Detection of Propaganda and Manipulation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00133091" target="_blank" >RIV/00216224:14330/23:00133091 - isvavai.cz</a>

  • Result on the web

    <a href="https://raslan2023.nlp-consulting.net/" target="_blank" >https://raslan2023.nlp-consulting.net/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Augmenting Stylometric Features to Improve Detection of Propaganda and Manipulation

  • Original language description

    Identification of manipulative techniques in newspaper texts allows an informed reader to cope with the text content without being negatively influenced. In this paper, we present new developments in using stylometry to support a deep learning neural network model in labelling newspaper articles for the presence of specific manipulative techniques. We also evaluate all stylometric features in 16 groups and improve the manipulation detection results in 15 of 17 techniques.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LM2018101" target="_blank" >LM2018101: Digital Research Infrastructure for the Language Technologies, Arts and Humanities</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the Seventeenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2023

  • ISBN

    9788026317937

  • ISSN

    2336-4289

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    67-77

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    Kouty nad Desnou

  • Event date

    Dec 8, 2023

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article