Finding Streams in Knowledge Graphs to Support Fact Checking

TL;DR

This paper introduces an unsupervised network-flow based method to assess the truthfulness of factual triples in knowledge graphs, aiding fact-checking by identifying relevant knowledge streams and patterns.

Contribution

A novel, unsupervised network-flow approach models knowledge as fluid flow to determine fact veracity and surface relevant information for fact checkers.

Findings

Outperforms existing algorithms on multiple datasets.

Effectively identifies true and false statements.

Discovers useful path patterns in knowledge graphs.

Abstract

The volume and velocity of information that gets generated online limits current journalistic practices to fact-check claims at the same rate. Computational approaches for fact checking may be the key to help mitigate the risks of massive misinformation spread. Such approaches can be designed to not only be scalable and effective at assessing veracity of dubious claims, but also to boost a human fact checker's productivity by surfacing relevant facts and patterns to aid their analysis. To this end, we present a novel, unsupervised network-flow based approach to determine the truthfulness of a statement of fact expressed in the form of a (subject, predicate, object) triple. We view a knowledge graph of background information about real-world entities as a flow network, and knowledge as a fluid, abstract commodity. We show that computational fact checking of such a triple then amounts to finding a "knowledge stream" that emanates from the subject node and flows toward the object node through paths connecting them. Evaluation on a range of real-world and hand-crafted datasets of facts related to entertainment, business, sports, geography and more reveals that this network-flow model can be very effective in discerning true statements from false ones, outperforming existing algorithms on many test cases. Moreover, the model is expressive in its ability to automatically discover several useful path patterns and surface relevant facts that may help a human fact checker corroborate or refute a claim.