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An Algorithm for the Detection of Hidden Propaganda in Mixed-Code Text over the Internet

Tundis, Andrea ; Mukherjee, Gaurav ; Mühlhäuser, Max (2021):
An Algorithm for the Detection of Hidden Propaganda in Mixed-Code Text over the Internet. (Publisher's Version)
In: Applied Sciences, 11 (5), MDPI, e-ISSN 2076-3417,
DOI: 10.26083/tuprints-00019316,

Available under: CC BY 4.0 International - Creative Commons, Attribution.

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Item Type: Article
Origin: Secondary publication via sponsored Golden Open Access
Status: Publisher's Version
Title: An Algorithm for the Detection of Hidden Propaganda in Mixed-Code Text over the Internet
Language: English

Internet-based communication systems have become an increasing tool for spreading misinformation and propaganda. Even though there exist mechanisms that are able to track unwarranted information and messages, users made up different ways to avoid their scrutiny and detection. An example is represented by the mixed-code language, that is text written in an unconventional form by combining different languages, symbols, scripts and shapes. It aims to make more difficult the detection of specific content, due to its custom and ever changing appearance, by using special characters to substitute for alphabet letters. Indeed, such substitute combinations of symbols, which tries to resemble the shape of the intended alphabet’s letter, makes it still intuitively readable to humans, however nonsensical to machines. In this context, the paper explores the possibility of identifying propaganda in such mixed-code texts over the Internet, centred on a machine learning based approach. In particular, an algorithm in combination with a deep learning models for character identification is proposed in order to detect and analyse whether an element contains propaganda related content. The overall approach is presented, the results gathered from its experimentation are discussed and the achieved performances are compared with the related works.

Journal or Publication Title: Applied Sciences
Volume of the journal: 11
Issue Number: 5
Publisher: MDPI
Collation: 22 Seiten
Classification DDC: 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
Divisions: 20 Department of Computer Science > Telecooperation
Date Deposited: 24 Aug 2021 07:30
Last Modified: 24 Aug 2021 07:31
DOI: 10.26083/tuprints-00019316
Corresponding Links:
URN: urn:nbn:de:tuda-tuprints-193167
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/19316
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