In examining the current landscape of anti-disinformation research, Maite Taboada argues that social media companies sharing larger data samples with researchers could help efforts to distinguish between true and false information through language and text analysis.
Maite Taboada is professor in the Department of Linguistics and associate member in the School of Computing Science at Simon Fraser University. She is a linguist working at the intersection of discourse analysis and computational linguistics. In discourse analysis, her research addresses the mechanisms for coherence in discourse, focusing on how links across sentences produce the impression of coherence in text and speech. In computational linguistics, she develops methods and algorithms to process and exploit discourse structure in different applications, especially for sentiment analysis. Current research projects involve analyses of online comments, with the goal of building a moderation platform to feature constructive comments more prominently; and a study of the language of misinformation, using text classification techniques to distinguish “fake” and fact-based news stories. Her lab, the Discourse Processing Lab at SFU is also collaborating with Informed Opinions. Together, they have built the Gender Gap Tracker, an online tool to track the number of men and women quoted in Canadian mainstream news media.