University of Sheffield researchers Yida Mu and Dr. Nikos Aletra report they’ve developed an artificial intelligence system to help identify Twitter users who are more likely to share unreliable news sources.
In their study published in the journal PeerJ Computer Science, the researchers found strong correlations between specific language patterns and the propensity to share false information.
Users who shared dubious information tended to use the words, “media,” “government,” “truth,” “Israel,” “liberal,” “muslim” and “Islam” in their tweets. Users who shared more reliable information sources tended to use more personal words such as “myself,” “feel,” “excited,” “mood,” “mom” and “okay.”
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