AllegatorTrack: Combining and reporting results of truth discovery from multi-source data

In the Web, a massive amount of user-generated contents is available through various channels, e.g., texts, tweets, Web tables, databases, multimedia-sharing platforms, etc. Conflicting information, rumors, erroneous and fake contents can be easily spread across multiple sources, making it hard to distinguish between what is true and what is not. How do you figure out that a lie has been told often enough that it is now considered to be true? How many lying sources are required to introduce confusion in what you knew before to be the truth? To answer these questions, we present AllegatorTrack, a system that discovers true claims among conflicting data from multiple sources.