Thesis Defence: Identifying Anger in Digital Spaces

Clare Wiznura, supervised by Dr. Christine Schreyer, will defend their thesis titled “Identifying Anger in Digital Spaces” in partial fulfillment of the requirements for the degree of Master of Arts in Interdisciplinary Graduate Studies – Digital Arts and Humanities theme.

An abstract for Clare Wiznura’s thesis is included below.

Defences are open to all members of the campus community as well as the general public. Registration is not required to attend in-person; however, please email christine.schreyer@ubc.ca to receive the Zoom link for this defence.

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Abstract

This thesis examines expressions and interpretations of anger in computer-mediated-communication (CMC) and identifies specific tactics and important factors in this expression and interpretation. This research is based on online data collection and a subsequent online survey.

The data collection portion of the research consisted of gathering samples of expressions of anger from social media platforms Reddit, YouTube, and TikTok. The samples were all gathered from discussions regarding the Canadian Housing Crisis. These samples were categorized and co-validated into different types of anger, and then analyzed for trends in specific textisms (linguistic features characteristic of CMC). Patterns in linguistic features found from this process were then used to create an online survey. The survey provided more detailed information for how CMC users interpret and express anger and yielded a total of 90 responses. The survey consisted of four major sections: data validation, where participants were asked to categorize samples from the previous data collection, roleplay, where participants were asked to type out what they angry message would be sent in response to a specific prompt, ranking, where participants ranked the emotional expression of a message with varying textisms, and analysis, where participants were provided texts asked to identify why this would be interpreted as angry or not.

The data collection and survey both found that specific features, specifically using a period for the final sentence in a message and quotation marks, are the features that are most interpreted as indicating anger. However, the features of expressions of anger across both the data collection and the survey also included questions, but this did not affect the interpretation of anger. This research finds that the most critical feature to interpreting and expressing anger is context. Overall, this thesis discusses the ways that CMC users interpret and express anger and the ways in which gender interact with this expression and interpretation, as well as highlights the large role context plays in interpretation of anger in CMC.