Computational Detection and Analysis of Manipulation Techniques in News Channels on Telegram in Ukraine

Volkova, Nataliia

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dc.contributor.author	Volkova, Nataliia
dc.date.accessioned	2024-08-26T11:48:09Z
dc.date.available	2024-08-26T11:48:09Z
dc.date.issued	2024
dc.identifier.citation	Volkova Nataliia. Computational Detection and Analysis of Manipulation Techniques in News Channels on Telegram in Ukraine. Ukrainian Catholic University, Faculty of Applied Sciences, Department of Computer Sciences. Lviv 2024, 36 p.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4681
dc.language.iso	en	uk
dc.subject	Computational Detection	uk
dc.subject	Analysis of Manipulation Techniques	uk
dc.subject	News Channels on Telegram	uk
dc.subject	Ukraine	uk
dc.subject	Telegram	uk
dc.title	Computational Detection and Analysis of Manipulation Techniques in News Channels on Telegram in Ukraine	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	In this research, we aim to identify specific instances of manipulation techniques such as doubts, black-and-white fallacy, appeal to fear, and loaded language and their granularity in news text from social media. To achieve this, we developed our own manually annotated corpus with 1,877 posts from Ukrainian news chan- nels on Telegram, all in the Ukrainian language, consisting of 3,472 manipulation techniques. Each annotation includes the fragment or span where a manipulation technique is detected, along with the corresponding technique from a set of selected techniques. We then trained a pre-trained BERT model to recognize these spans and their associated manipulation techniques. Additionally, we generated syntactic data to enhance the model’s performance.	uk