Using Linguistic and Stylometric Features for Satirical News Detection in Bahasa Indonesia

Sari, Yunita and Hastuti, Rochana Prih and Herwanto, Guntur Budi (2023) Using Linguistic and Stylometric Features for Satirical News Detection in Bahasa Indonesia. In: 10th International Conference on Computer, Control, Informatics and its Applications, IC3INA 2023, 4 October 2023through 5 October 2023, Virtual, Online.

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Abstract

In this paper, we present our work on satirical news detection for Indonesian. Despite the progress of satirical news detection in English, there has been lack of research work for other languages including Indonesian. We start this research by developing INSIDE, a novel dataset for Indonesian Satirical News Detection. The dataset consists of 100 satirical news and 190 its corresponding real news articles that were collected from satirical source and various legitimate online sites. INSIDE is one of the efforts to encourage more research in low-resource language. It also enrich real-world data source for developing cross-lingual model in the area of satirical news detection. Further to dataset development, we conducted experiment on satirical news detection using various linguistic and stylometric features. Results show the effectiveness of our model. In addition to that, certain features such as bag-of-words, writing style and structural features are found to be beneficial for detecting satirical news

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bahasa Indonesia; Satirical News Detection; Stylometric
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Mathematics and Natural Sciences > Computer Science & Electronics Department
Depositing User: Ismu WIDARTO
Date Deposited: 04 Sep 2024 05:59
Last Modified: 04 Sep 2024 05:59
URI: https://ir.lib.ugm.ac.id/id/eprint/6354

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