Social Movement Sustainability on Social Media: An Analysis of the Women’s March Movement on Twitter
Abstract
Social media has emerged as a powerful medium to organize and mobilize social movements. In particular, the connective action of social media builds associations and allows for the continuity of social movements. Yet there is a lack of research on how connective action emergent from social media messages sustains long-term social movements. Accordingly, in this study, we concentrate on Twitter messages related to Women’s March protests held in 2017, 2018, and 2019. Using an interpretive analysis followed by the topic modeling approach, we analyzed the tweets to identify the different types of messages associated with the movement. These messages were classified using a set of categories and subcategories. Furthermore, we conducted a temporal analysis of the message (sub)categories to understand how distinct messages allow movement continuity beyond a specific protest march. Results suggest that while most of the messages are used to motivate and mobilize individuals, the connective action tactics employed through messages sent before, during, and after the marches allowed Women’s March to become a broader and more persistent movement. We advance theoretical propositions to explain the sustainability of a long-term social movement on social media, exemplified through large-scale connective action that persists over time. In doing so, this study contributes to connective action research by providing message categorization that synthesizes the meaning of message content. The findings could help social movement organizers learn different ways to frame messages that resonate with broader social media users. Moreover, our approach to analyzing a large set of tweets might interest other qualitative researchers.
Recommended Citation
Syed, Romilla and Silva, Leiser
(2023)
"Social Movement Sustainability on Social Media: An Analysis of the Women’s March Movement on Twitter,"
Journal of the Association for Information Systems, 24(1), 249-293.
DOI: 10.17705/1jais.00776
Available at:
https://aisel.aisnet.org/jais/vol24/iss1/2
DOI
10.17705/1jais.00776
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