Repurposing sentiment analysis for social research scopes : an inquiry into emotion expression within affective publics on Twitter during the Covid-19 emergency

Rathnayake, Chamil and Caliandro, Alessandro; Toeppe, Katharina and Yan, Hui and Chu, Samuel Kai, eds. (2021) Repurposing sentiment analysis for social research scopes : an inquiry into emotion expression within affective publics on Twitter during the Covid-19 emergency. In: Diversity, Divergence, Dialogue - 16th International Conference, iConference 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer, CHN, pp. 396-410. ISBN 978-3-030-71292-1

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    Abstract

    The scope of the article is to discuss and propose some methodological strategies to repurpose sentiment analysis for social research scopes. We argue that sentiment analysis is well suited to study an important topic in digital sociology: affective publics. Specifically, sentiment analysis reveals useful to explore two key components of affective publics: a) structure (emergence of dominant emotions); b) dynamics (transformation of affectivity into emotions). To do that we suggest combining sentiment analysis with emotion detection, text analysis and social media engagement metrics – which help to better understand the semantic and social context in which the sentiment related to a specific issue is situated. To illustrate our methodological point, we draw on the analysis of 33,338 tweets containing two hashtags – #NHSHeroes and #Covidiot – emerged in response to the global pandemic caused by Covid-19. Drawing on the analysis of the two affective publics aggregating around #NHSHeroes and #Covidiot, we conclude that they reflect a blend of emotions. In some cases, such generic flow of affect coalesces into a dominant emotion while it may not necessarily occur in other instances. Affective publics structured around positive emotions and local issues tend to be more consistent and cohesive than those based on general issues and negative emotions. Although negative emotions might attract the attention of digital publics, positively framed messages engage users more.

    ORCID iDs

    Rathnayake, Chamil ORCID logoORCID: https://orcid.org/0000-0003-1964-2639 and Caliandro, Alessandro; Toeppe, Katharina, Yan, Hui and Chu, Samuel Kai