Abstract
Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation.
Highlights
Online communication platforms, in particular social media, have created a situation in which the proverbial lie “can travel the world before the truth can get its boots on.” Misinformation [1], astroturf [2], spam [3], and outright fraud [4] have become widespread
The transitive closure of G is GÃ = (V, EÃ) where the set of edges is closed under adjacency, that is, two nodes are adjacent in GÃ iff they are connected in G via at least one path. This standard notion of closure has been extended to weighted graphs, allowing adjacency to be generalized by measures of path length [27], such as the semantic proximity for the Wikipedia Knowledge Graph (WKG) we introduce
Our fact-checking method requires that we define a measure of path semantic proximity by selecting a transitive closure algorithm and a directed or undirected WKG representation
Summary
In particular social media, have created a situation in which the proverbial lie “can travel the world before the truth can get its boots on.” Misinformation [1], astroturf [2], spam [3], and outright fraud [4] have become widespread. Misinformation [1], astroturf [2], spam [3], and outright fraud [4] have become widespread They are seemingly unavoidable components of our online information ecology [5] that jeopardize our ability as a society to make rapid and informed decisions [6,7,8,9,10]. Wikipedia, the crowd-sourced online encyclopedia, has been shown to be nearly as reliable as traditional encyclopedias, even though it covers many more topics [17] It serves as a large-scale knowledge repository for millions of individuals, who can contribute to its content in an open way. Its continuous editing process even indicates signs of collective human intelligence [19]
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