@inproceedings{subramanian-etal-2024-overview,
title = "Overview of the Second Shared Task on Fake News Detection in {D}ravidian Languages: {D}ravidian{L}ang{T}ech@{EACL} 2024",
author = "Subramanian, Malliga and
Chakravarthi, Bharathi Raja and
Shanmugavadivel, Kogilavani and
Pandiyan, Santhiya and
Kumaresan, Prasanna Kumar and
Palani, Balasubramanian and
B, Premjith and
K, Vanaja and
S, Mithunja and
K, Devika and
S.b, Hariprasath and
B, Haripriya and
E, Vigneshwar",
editor = "Chakravarthi, Bharathi Raja and
Priyadharshini, Ruba and
Madasamy, Anand Kumar and
Thavareesan, Sajeetha and
Sherly, Elizabeth and
Nadarajan, Rajeswari and
Ravikiran, Manikandan",
booktitle = "Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages",
month = mar,
year = "2024",
address = "St. Julian's, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.dravidianlangtech-1.11",
pages = "71--78",
abstract = "The rise of online social media has revolutionized communication, offering users a convenient way to share information and stay updated on current events. However, this surge in connectivity has also led to the proliferation of misinformation, commonly known as fake news. This misleading content, often disguised as legitimate news, poses a significant challenge as it can distort public perception and erode trust in reliable sources. This shared task consists of two subtasks such as task 1 and task 2. Task 1 aims to classify a given social media text into original or fake. The goal of the FakeDetect-Malayalam task2 is to encourage participants to develop effective models capable of accurately detecting and classifying fake news articles in the Malayalam language into different categories like False, Half True, Mostly False, Partly False, and Mostly True. For this shared task, 33 participants submitted their results.",
}
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<abstract>The rise of online social media has revolutionized communication, offering users a convenient way to share information and stay updated on current events. However, this surge in connectivity has also led to the proliferation of misinformation, commonly known as fake news. This misleading content, often disguised as legitimate news, poses a significant challenge as it can distort public perception and erode trust in reliable sources. This shared task consists of two subtasks such as task 1 and task 2. Task 1 aims to classify a given social media text into original or fake. The goal of the FakeDetect-Malayalam task2 is to encourage participants to develop effective models capable of accurately detecting and classifying fake news articles in the Malayalam language into different categories like False, Half True, Mostly False, Partly False, and Mostly True. For this shared task, 33 participants submitted their results.</abstract>
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%0 Conference Proceedings
%T Overview of the Second Shared Task on Fake News Detection in Dravidian Languages: DravidianLangTech@EACL 2024
%A Subramanian, Malliga
%A Chakravarthi, Bharathi Raja
%A Shanmugavadivel, Kogilavani
%A Pandiyan, Santhiya
%A Kumaresan, Prasanna Kumar
%A Palani, Balasubramanian
%A B, Premjith
%A K, Vanaja
%A S, Mithunja
%A K, Devika
%A S.b, Hariprasath
%A B, Haripriya
%A E, Vigneshwar
%Y Chakravarthi, Bharathi Raja
%Y Priyadharshini, Ruba
%Y Madasamy, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Sherly, Elizabeth
%Y Nadarajan, Rajeswari
%Y Ravikiran, Manikandan
%S Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F subramanian-etal-2024-overview
%X The rise of online social media has revolutionized communication, offering users a convenient way to share information and stay updated on current events. However, this surge in connectivity has also led to the proliferation of misinformation, commonly known as fake news. This misleading content, often disguised as legitimate news, poses a significant challenge as it can distort public perception and erode trust in reliable sources. This shared task consists of two subtasks such as task 1 and task 2. Task 1 aims to classify a given social media text into original or fake. The goal of the FakeDetect-Malayalam task2 is to encourage participants to develop effective models capable of accurately detecting and classifying fake news articles in the Malayalam language into different categories like False, Half True, Mostly False, Partly False, and Mostly True. For this shared task, 33 participants submitted their results.
%U https://aclanthology.org/2024.dravidianlangtech-1.11
%P 71-78
Markdown (Informal)
[Overview of the Second Shared Task on Fake News Detection in Dravidian Languages: DravidianLangTech@EACL 2024](https://aclanthology.org/2024.dravidianlangtech-1.11) (Subramanian et al., DravidianLangTech-WS 2024)
ACL
- Malliga Subramanian, Bharathi Raja Chakravarthi, Kogilavani Shanmugavadivel, Santhiya Pandiyan, Prasanna Kumar Kumaresan, Balasubramanian Palani, Premjith B, Vanaja K, Mithunja S, Devika K, Hariprasath S.b, Haripriya B, and Vigneshwar E. 2024. Overview of the Second Shared Task on Fake News Detection in Dravidian Languages: DravidianLangTech@EACL 2024. In Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, pages 71–78, St. Julian's, Malta. Association for Computational Linguistics.