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Cited by 317

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement

Xiong, Ying, Cho, Moonhee, Boatwright, Brandon·2019·Public Relations Review
DOI 10.1016/j.pubrev.2018.10.014
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Abstract

Abstract During the #MeToo movement, social movement organizations (SMOs) played a crucial role in the online mobilization by utilizing various message frames and appealing hashtags during the social movement. Applying a co-creational approach and using framing as a theoretical framework, the study explored how SMOs use words and hashtags to participate in the #MeToo movement through Twitter. Based on both semantic network analysis and thematic analysis methods, findings of the study enhance literature of social movement organizations and activism as well as provide practical implications for effective social movement campaigns.

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Metadata

Authors
Xiong, Y., Cho, M., & Boatwright, B.
Venue
Public Relations Review
Publisher
Elsevier BV
Published
2019-03
Volume
45
Issue
1
Pages
10-23
ISSN
0363-8111 (ISSN-L)
DOI
10.1016/j.pubrev.2018.10.014
OpenAlex
W2901886042
Cited by
317
References
85
FWCI
63.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement. https://app.cochat.ai/papers/10.1016/j.pubrev.2018.10.014
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Xiong, Y., Cho, M., & Boatwright, B. (2019). Hashtag activism and message frames among social movement organizations: Semantic network analysis and thematic analysis of Twitter during the #MeToo movement. Public Relations Review. https://doi.org/10.1016/j.pubrev.2018.10.014

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.