Exploring the Utilization of Hashtags in Cancel Culture Messaging: A Natural Language Processing Dictionary Analysis Approach

This study employs a natural language processing (NLP) dictionary analysis to examine the dynamics of cancel culture discourse through hashtag usage. As a form of digital activism characterized by public condemnation and ostracization, cancel culture relies heavily on hashtags to mobilize engagement and amplify messages. This study identifies prevailing themes within cancel culture conversations by analyzing hashtags associated with related tweets. Using a dictionary-based NLP approach, hashtags are categorized into recurring thematic clusters such as social justice, celebrity controversies, nationalism, and political activism. Proportional analysis of these clusters illustrates the dominant issues shaping cancel culture discourse across six countries—Australia, South Korea, the United States, the United Kingdom, Nigeria, and Brazil—highlighting both shared patterns and context-specific variations.