KnowTellConvince at ArAIEval shared task: disinformation and persuasion detection in Arabic using similar and contrastive representation alignment

Hariram Veeramani, Surendrabikram Thapa, Usman Naseem

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)

Abstract

In an era of widespread digital communication, the challenge of identifying and countering disinformation has become increasingly critical. However, compared to the solutions available in the English language, the resources and strategies for tackling this multifaceted problem in Arabic are relatively scarce. To address this issue, this paper presents our solutions to tasks in ArAIEval 2023. Task 1 focuses on detecting persuasion techniques, while Task 2 centers on disinformation detection within Arabic text. Leveraging a multi-head model architecture, fine-tuning techniques, sequential learning, and innovative activation functions, our contributions significantly enhance persuasion techniques and disinformation detection accuracy. Beyond improving performance, our work fills a critical research gap in content analysis for Arabic, empowering individuals, communities, and digital platforms to combat deceptive content effectively and preserve the credibility of information sources within the Arabic-speaking world.

Original languageEnglish
Title of host publicationProceedings of ArabicNLP 2023
Place of PublicationStroudsburg
PublisherAssociation for Computational Linguistics (ACL)
Pages519-524
Number of pages6
ISBN (Electronic)9781959429272
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event1st Arabic Natural Language Processing Conference, ArabicNLP 2023 - Hybrid, Singapore, Singapore
Duration: 7 Dec 20237 Dec 2023

Conference

Conference1st Arabic Natural Language Processing Conference, ArabicNLP 2023
Country/TerritorySingapore
CityHybrid, Singapore
Period7/12/237/12/23

Fingerprint

Dive into the research topics of 'KnowTellConvince at ArAIEval shared task: disinformation and persuasion detection in Arabic using similar and contrastive representation alignment'. Together they form a unique fingerprint.

Cite this