Span identification and technique classification of propaganda in news articles

Li, W; Li, S; Liu, C; Lu, L; Shi, Z; Wen, S

Span identification and technique classification of propaganda in news articles

Li, W Li, S Liu, C Lu, L Shi, Z Wen, S

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Publisher:: Springer
Publication Type:: Journal Article
Citation:: Complex and Intelligent Systems, 2022, 8, (5), pp. 3603-3612
Issue Date:: 2022-05-08

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Field	Value	Language
dc.contributor.author	Li, W
dc.contributor.author	Li, S
dc.contributor.author	Liu, C
dc.contributor.author	Lu, L
dc.contributor.author	Shi, Z
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.date.accessioned	2023-03-13T12:59:38Z
dc.date.available	2023-03-13T12:59:38Z
dc.date.issued	2022-05-08
dc.identifier.citation	Complex and Intelligent Systems, 2022, 8, (5), pp. 3603-3612
dc.identifier.issn	2199-4536
dc.identifier.issn	2198-6053
dc.identifier.uri	http://hdl.handle.net/10453/167174
dc.description.abstract	Propaganda is a rhetorical technique designed to serve a specific topic, which is often used purposefully in news article to achieve our intended purpose because of its specific psychological effect. Therefore, it is significant to be clear where and what propaganda techniques are used in the news for people to understand its theme efficiently during our daily lives. Recently, some relevant researches are proposed for propaganda detection but unsatisfactorily. As a result, detection of propaganda techniques in news articles is badly in need of research. In this paper, we are going to introduce our systems for detection of propaganda techniques in news articles, which is split into two tasks, Span Identification and Technique Classification. For these two tasks, we design a system based on the popular pretrained BERT model, respectively. Furthermore, we adopt the over-sampling and EDA strategies, propose a sentence-level feature concatenating method in our systems. Experiments on the dataset of about 550 news articles offered by SEMEVAL show that our systems perform state-of-the-art.
dc.language	en
dc.publisher	Springer
dc.relation.ispartof	Complex and Intelligent Systems
dc.relation.isbasedon	10.1007/s40747-021-00393-y
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Span identification and technique classification of propaganda in news articles
dc.type	Journal Article
utslib.citation.volume	8
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2023-03-13T12:59:37Z
pubs.issue	5
pubs.publication-status	Accepted
pubs.volume	8
utslib.citation.issue	5

Abstract:

Propaganda is a rhetorical technique designed to serve a specific topic, which is often used purposefully in news article to achieve our intended purpose because of its specific psychological effect. Therefore, it is significant to be clear where and what propaganda techniques are used in the news for people to understand its theme efficiently during our daily lives. Recently, some relevant researches are proposed for propaganda detection but unsatisfactorily. As a result, detection of propaganda techniques in news articles is badly in need of research. In this paper, we are going to introduce our systems for detection of propaganda techniques in news articles, which is split into two tasks, Span Identification and Technique Classification. For these two tasks, we design a system based on the popular pretrained BERT model, respectively. Furthermore, we adopt the over-sampling and EDA strategies, propose a sentence-level feature concatenating method in our systems. Experiments on the dataset of about 550 news articles offered by SEMEVAL show that our systems perform state-of-the-art.

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http://hdl.handle.net/10453/167174