Our society is struggling with an unprecedented amount of falsehoods, hyperboles, and half-truths. Politicians and organizations repeatedly make the same false claims. Fake news floods the cyberspace and even allegedly influenced the 2016 election. In fighting false information, the number of active fact-checking organizations has grown from 44 in 2014 to 114 in early 2017. 1 Fact-checkers vet claims by investigating relevant data and documents and publish their verdicts. For instance, PolitiFact.com, one of the earliest and most popular fact-checking projects, gives factual claims truthfulness ratings such as True, Mostly True, Half true, Mostly False, False, and even "Pants on Fire". In the U.S., the election year made fact-checking a part of household terminology. For example, during the first presidential debate on September 26, 2016, NPR.org's live fact-checking website drew 7.4 million page views and delivered its biggest traffic day ever.

We present ClaimPortal, a web-based platform for monitoring, searching, checking, and analyzing English factual claims on Twitter. We explain the architecture of ClaimPortal, its components and functions, and the user interface. While the last several years have witnessed a substantial growth in interests and efforts in the area of computational factchecking, ClaimPortal is a novel infrastructure in that fact-checkers have largely skipped factual claims in tweets. It can be a highly powerful tool to both general web users and factcheckers. It will also be an educational resource in helping cultivate a society that is less susceptible to falsehoods. While it currently focuses on politics-related tweets, it will be extended to include more general factual claims.

This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of, and effective interventions against the COVID-19 misinfodemic on Twitter. Specifically, it introduces a public dashboard which, in addition to displaying case counts in an interactive map and a navigational panel, also provides some unique features not found in other places. Particularly, the dashboard uses a curated catalog of COVID-19 related facts and debunks of misinformation, and it displays the most prevalent information from the catalog among Twitter users in user-selected U.S. geographic regions. The paper explains how to use BERT-based models to match tweets with the facts and misinformation and to detect their stance towards such information. The paper also discusses the results of preliminary experiments on analyzing the spatiotemporal spread of misinformation.