Opposites Attract? Ambivalence in Distinguishing Real and Fake News and Predicting their Spread

Abstract

This study expands the understanding of linguistic cues in fake news by exploring ambivalent language's role in distinguishing real from fake news and its impact on news spread. Unlike prior research focusing on positive or negative language separately, this work hypothesizes that fake news may exhibit higher ambivalence, aligning with its association with high-arousal emotions and writers' efforts to attract attention. Ambivalence, traditionally viewed as the co-occurrence of conflicting positive and negative elements, is extended here to include diverse dimensions such as textual, temporal, psychological, and content-related ambivalence.