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Characterizing the Impact of Influential Actors on the Dynamics of #MeToo Online Social Movement

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Partially supported by a NULab Seedling Grant.

Decentralized social movements, such as those mediated through social networks, follow a model of open engagement. Various groups can engage with the movement while focusing on multiple related topics and concerns. Additionally, the engagement of some groups may impact the participation of others. The #MeToo movement has been studied from various perspectives, including recent work examining the participation of different intersectional identities. However, little is known about the role and impact of highly influential actors such as institutions, organizations, brands, and public figures, on online social movements. These actors have wide reaching audiences and tend to have an outsize impact in the public discourse. However, much remains unknown about how these actors decide whether (and when) to get involved in such movements, and how their participation impacts the dynamics of decentralized, heterogeneous online social movements. On the one hand, influential actors can be central nodes that bridge communities that would otherwise be disconnected, thus helping to amplify social movements. On the other hand, their involvement may bring other interests to the discussion which can alienate or discourage participation from some individuals or groups that were actively engaging with the movement before that involvement.

This work analyzes the impact of influential actors in the dynamics of the #MeToo movement. Specifically, it addresses the following research questions: (i) how have influential actors engaged with the movement over time? and (ii) what was the impact of influential actors on the participation of other groups? To answer these questions, the project leverages computational linguistic and demographic inference methods to analyze a longitudinal dataset of more than nine million news articles and social media posts about the #MeToo movement spanning a period of five years (2015-20).

Principal Investigator

Silvio Amir, Faculty, Computer Science

Collaborators

Yakov Bart, Faculty, Marketing; Michael Manzon, Student Researcher, Computer Science; Sean O’Hara, Student Researcher, Finance

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