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This study explores the framing strategies and language features of U.S. news coverage surrounding sexual violence and gender issues across the ideological media spectrum at two pivotal phases of the #MeToo movement: (1) during its initial rise as a hashtag-driven social movement in 2017 and (2) during the Kavanaugh nomination and confirmation in 2018. Using structural topic modeling, community detection, and feature extraction, we reveal a heightened employment of political framing during the Kavanaugh accusations. Topical prevalence and language use in news treatment also showed clear partisan differences, consistent with theories of moral foundation and issue ownership. Implications for research on news coverage of gender rights and framing of social movements are discussed. [ABSTRACT FROM AUTHOR]

Garnering coverage across the political spectrum is a major challenge for burgeoning social movements. The #MeToo movement stands out due to the volume of attention it generated. Yet, it is unclear how news media across the partisan spectrum covered the movement using different sexual violence language markers, latent topic, and word choices and which accusations and events drove media attention. To examine this, we used Media Cloud to extract 17,877 news articles from nine media outlets across the political spectrum, containing specific n-grams or co-occurrences of (1) "metoo," (2) "sexual misconduct," (3) "sexual harassment," and (4) "sexual assault" from October 2017 through February 2018. The analyses first examined whether language and attention differed across the ideological news ecology and then turned to time-series modeling of these discourses to examine what drove press coverage and structural topic modeling (STM) and term frequency-inverse document frequency (TF-IDF) analysis to understand latent topics and language usage. Findings reveal that (1) left-leaning media dedicated more relative attention across all topics—#MeToo, sexual misconduct, sexual harassment, and sexual assault—relative to centrist and right-leaning media. Moreover, across the right, left, and centrist media, the language markers "misconduct," "harassment," and "assault" decreased over the study period, while the mentions of #MeToo movement increased during the same period; (2) stories relating to entertainment and those accusing politicians, especially those belonging to the party in power at the Federal level, seemed to be by far the strongest driver of news media attention; and (3) we further observed partisan differences in topics of news coverage and language usage. [ABSTRACT FROM AUTHOR]

How did efforts that prompted the sharing of personal experiences of sexual violence and harassment around #MeToo coalesce into calls for action across a range of institutions and communities? We argue that sharing experiences of trauma in digital spaces created a network of acknowledgment, which supported and sustained nascent #MeToo activism based on the logic of connective action. This article attempts to (a) understand the temporal dynamics of these different discourses within the #MeToo movement on Twitter, (b) reveal the accounts animating these discourses and the most prominent themes within them, and (c) model the overtime relationship between these discourses and their relationship to major news event and #MeToo revelations. To do so, we analyze a 1% sample of tweets from the 5-month period following the revelations about Harvey Weinstein in early October 2017, employing a range of computational approaches, including part-of-speech tagging, dependency analysis, hashtags extraction, and retweet network analysis—to identify key discourses, actors, and themes. We then conduct time series analysis to identify the relationship between the two discourses and predict how the ebbs and flows of each discourse are shaped by news events. [ABSTRACT FROM AUTHOR]