Recognition of propaganda techniques in newspaper texts: Fusion of content and style analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ASJ4IZL2C" target="_blank" >RIV/00216208:11320/25:SJ4IZL2C - isvavai.cz</a>
Alternative codes found
RIV/00216224:14330/24:00135846
Result on the web
<a href="https://www.webofscience.com/wos/woscc/summary/80725160-5a91-43b8-9a0c-c1eadd4658ae-fed151e5/relevance/1" target="_blank" >https://www.webofscience.com/wos/woscc/summary/80725160-5a91-43b8-9a0c-c1eadd4658ae-fed151e5/relevance/1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.eswa.2024.124085" target="_blank" >10.1016/j.eswa.2024.124085</a>
Alternative languages
Result language
angličtina
Original language name
Recognition of propaganda techniques in newspaper texts: Fusion of content and style analysis
Original language description
Public texts aiming at reader manipulation for propaganda or disinformation purposes pose a significant threat to society. The ability to detect the presence of a specific manipulative technique in a text offers an informed warning to readers and guides them to carefully judge the actual statement. In this article, we address the problem of developing new models capable of analyzing newspaper articles for propagandistic features. We introduce a new large dataset of manipulative techniques obtained via gathering and human annotation of 8,646 newspaper articles in Czech, which represents one of the former Soviet influence area languages. The dataset allows both to train new methods to recognize propaganda and disinformation and offer a general comparable benchmark for the techniques. We evaluate the dataset against selected state-of-the-art machine learning approaches to provide high-performing baselines for detecting seventeen annotated manipulative techniques. We also present thorough measurements of inter-annotator agreements that approximate the difficulty level of each of the attributes. As a new finding, we propose a set of text style analysis features that lean on the assumption that each manipulation leads to a specific style pattern. We show that the style analysis improves the detection results for most of the manipulative techniques. The viability of the approach is also confirmed on the well-known QProp propaganda dataset, providing new state-of-the-art results.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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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/LM2023062" target="_blank" >LM2023062: Digital Research Infrastructure for Language Technologies, Arts and Humanities</a><br>
Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
EXPERT SYSTEMS WITH APPLICATIONS
ISSN
0957-4174
e-ISSN
1873-6793
Volume of the periodical
251
Issue of the periodical within the volume
2024-10-01
Country of publishing house
US - UNITED STATES
Number of pages
11
Pages from-to
1-11
UT code for WoS article
001235661700001
EID of the result in the Scopus database
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