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Megha Sundriyal

5 accepted papers

2025

Parallel Communities Across the Surface Web and the Dark Web

EMNLP 2025

Humans have an inherent need for community belongingness. This paper investigates this fundamental social motivation by compiling a large collection of parallel datasets comprising over 7 million posts and comments from Reddit and 200,000 posts and comments from Dread, a dark web discussion forum, c

2025

The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detection

EMNLP 2025

Misinformation remains one of the most significant issues in the digital age. While automated fact-checking has emerged as a viable solution, most current systems are limited to evaluating factual accuracy. However, the detrimental effect of misinformation transcends simple falsehoods; it takes adva

Cited by 0SourcePDFScholar
2023

$\textit{From Chaos to Clarity}$: Claim Normalization to Empower Fact-Checking

EMNLP 2023long findings

With the rise of social media, users are exposed to many misleading claims. However, the pervasive noise inherent in these posts presents a challenge in identifying precise and prominent claims that require verification. Extracting the important claims from such posts is arduous and time-consuming,…

Cited by 0SourceScholar
2023

$\textit{Lost in Translation, Found in Spans}$: Identifying Claims in Multilingual Social Media

EMNLP 2023long main

Claim span identification (CSI) is an important step in fact-checking pipelines, aiming to identify text segments that contain a check-worthy claim or assertion in a social media post. Despite its importance to journalists and human fact-checkers, it remains a severely understudied problem, and the…

Cited by 0SourceScholar
2022

Empowering the Fact-checkers! Automatic Identification of Claim Spans on Twitter

EMNLP 2022main

The widespread diffusion of medical and political claims in the wake of COVID-19 has led to a voluminous rise in misinformation and fake news. The current vogue is to employ manual fact-checkers to efficiently classify and verify such data to combat this avalanche of claim-ridden misinformation. How…