论文标题
检查伴侣：优先考虑用户生成的多媒体内容以进行事实检查
Check Mate: Prioritizing User Generated Multi-Media Content for Fact-Checking
论文作者
论文摘要
社交媒体上的内容和错误信息的数量正在迅速增加。有必要通过确定需要检查事实的内容来支持事实检查器的系统。先前关于对事实核对内容进行优先级列表内容的研究重点是新闻媒体文章，主要是英语。越来越多地在用户生成的内容中发现错误信息。在本文中，我们提出了一个新颖的数据集，该数据集可用于优先考虑印地语中多媒体内容的值得检查的帖子。它在其1）关注用户生成的内容的1）中是独一无二的，2）语言和3）在社交媒体帖子中的多模式适应。此外，我们还为每个帖子提供元数据，例如流行的印度社交媒体平台Sharechat上的股票数量和诸如帖子的数量，可以围绕病毒性和错误信息进行相关分析。该数据可在Zenodo（https://zenodo.org/record/4032629）上访问，在Creative Commons Attribution许可（CC By 4.0）下可访问。
Volume of content and misinformation on social media is rapidly increasing. There is a need for systems that can support fact checkers by prioritizing content that needs to be fact checked. Prior research on prioritizing content for fact-checking has focused on news media articles, predominantly in English language. Increasingly, misinformation is found in user-generated content. In this paper we present a novel dataset that can be used to prioritize check-worthy posts from multi-media content in Hindi. It is unique in its 1) focus on user generated content, 2) language and 3) accommodation of multi-modality in social media posts. In addition, we also provide metadata for each post such as number of shares and likes of the post on ShareChat, a popular Indian social media platform, that allows for correlative analysis around virality and misinformation. The data is accessible on Zenodo (https://zenodo.org/record/4032629) under Creative Commons Attribution License (CC BY 4.0).
