Papers by Megha Sundriyal
Parallel Communities Across the Surface Web and the Dark Web (2025.findings-emnlp)
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Wenchao Dong, Megha Sundriyal, Seongchan Park, Jaehong Kim, Meeyoung Cha, Tanmoy Chakraborty, Wonjae Lee
| Challenge: | Sense of Community is a social motivation that is reflected in the social behavior of humans. |
| Approach: | They compile a large collection of parallel community datasets comprising over 7 million posts and comments from Reddit and 200,000 posts and comment from Dread, a dark web discussion forum, covering similar topics. |
| Outcome: | The results show that users on Reddit exhibit a stronger sense of community membership despite the dark web’s restricted accessibility. |
From Chaos to Clarity: Claim Normalization to Empower Fact-Checking (2023.findings-emnlp)
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| Challenge: | Social media posts are noisy and pervasive, resulting in difficult to identify precise and prominent claims that require verification. |
| Approach: | They propose a task called Claim Normalization that decomposes complex and noisy social media posts into more straightforward and understandable forms, termed normalized claims. |
| Outcome: | The proposed model outperforms baselines across evaluation measures and errors. |
LESA: Linguistic Encapsulation and Semantic Amalgamation Based Generalised Claim Detection from Online Content (2021.eacl-main)
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| Challenge: | Existing work on claim detection is built on the basis of a 'segregation' of claims across different domains. |
| Approach: | They propose a generalized generalized model that captures syntactic features through part-of-speech and dependency embeddings, as well as contextual features through a fine-tuned language model. |
| Outcome: | The proposed model outperforms baselines on six claim datasets by an average of 3 claim-F1 points and 2 claim-f1 points on the general-domain experiments. |
The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detection (2025.emnlp-main)
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Arghodeep Nandi, Megha Sundriyal, Euna Mehnaz Khan, Jikai Sun, Emily K. Vraga, Jaideep Srivastava, Tanmoy Chakraborty
| Challenge: | a survey examines the interplay between factual accuracy and cognitive biases . misinformation is more than just the existence of incorrect information, it also entails complex relationships between the information and the entities that consume it. |
| Approach: | They examine the interplay between traditional fact-checking and psychological concepts such as cognitive biases, social dynamics, and emotional responses. |
| Outcome: | The findings highlight limitations of current methods and identify opportunities for improvement . they also outline future research directions to create more robust frameworks . |
Lost in Translation, Found in Spans: Identifying Claims in Multilingual Social Media (2023.emnlp-main)
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| Challenge: | Claim span identification (CSI) is an important step in fact-checking pipelines . despite its importance to journalists and fact-seekers, it remains a understudied problem . |
| Approach: | They propose to use social media claims to identify text segments that contain a check-worthy claim or assertion in a social media post. |
| Outcome: | The proposed dataset outperforms other cross-lingual transfer methods on multiple languages. |
Empowering the Fact-checkers! Automatic Identification of Claim Spans on Twitter (2022.emnlp-main)
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| Challenge: | Current vogue is to employ manual fact-checkers to efficiently classify and verify such data to combat this avalanche of misinformation and fake news. |
| Approach: | They propose a large-scale Twitter corpus with token-level claim spans on more than 7.5k tweets and a model that automatically detects and extracts the snippets of misinformation. |
| Outcome: | The proposed model outperforms baseline systems on several evaluation metrics, improving by 1.5 points. |