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Automated fact-checking has drawn considerable attention over the past fewdecades due to the increase in the diffusion of misinformation on onlineplatforms. This is often carried out as a sequence of tasks comprising (i) thedetection of sentences circulating in online platforms which constitute claimsneeding verification, followed by (ii) the verification process of thoseclaims. This survey focuses on the former, by discussing existing effortstowards detecting claims needing fact-checking, with a particular focus onmultilingual data and methods. This is a challenging and fertile directionwhere existing methods are yet far from matching human performance due to theprofoundly challenging nature of the issue. Especially, the dissemination ofinformation across multiple social platforms, articulated in multiple languagesand modalities demands more generalized solutions for combating misinformation.Focusing on multilingual misinformation, we present a comprehensive survey ofexisting multilingual claim detection research. We present state-of-the-artmultilingual claim detection research categorized into three key factors of theproblem, verifiability, priority, and similarity. Further, we present adetailed overview of the existing multilingual datasets along with thechallenges and suggest possible future advancements.

Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Research