Since Occupy Wall Street began in New York City on September 17th, the movement has spread offline to hundreds of locations around the globe. Social networking sites have been critical for linking potential supporters and distributing information. In addition to Facebook pages on the Wall Street Occupation, more than 400 unique pages have been established in order to spread the movement across the US, including at least one page in each of the 50 states. These Facebook pages facilitate the creation of local encampments and the organization of protests and marches to oppose the existing economic and political system. 'Based on data acquired from Facebook, we find that Occupy groups have recruited over 170,000 active Facebook users and more than 1.4 million “likes” in support of Occupations. By October 22, Facebook pages related to the Wall Street Occupation had accumulated more than 390,000 “likes”, while almost twice that number, more than 770,000, have been expressed for the 324 local sites. Most new Occupation pages were started between September 23th and October 5th. On October 11th, occupy activity on Facebook peaked with 73,812 posts and comments to an occupy page in a day. By October 22nd, there had been 1,170,626 total posts or comments associated with Occupation pages. The density of Facebook activism is highest in college towns and in state capitals. Major uses for Facebook within the movement include the recruitment of people and resources to local occupations; information sharing and story telling; and across-group exchanges. While the focus of Occupy Wall Street is on mobilizing individual’s offline, online activities greatly facilitate these efforts.

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The past few years have seen a resurgence of right-wing demonstrations in the United States. Using new protest event data collected by the Crowd Counting Consortium, this visualization presents monthly trends in the size and count of protests by topic between 2017 and 2022. Conservative protest in the first three years was at a notably low level but with some very large events and a focus on abortion and gun rights. Protests swelled, starting in 2020, with demonstrations against coronavirus disease 2019 restrictions and in support of police officers, followed by election fraud rallies. Finally, 2022 was marked by lower levels of participation overall and increased events targeting LGBQT+ rights.

Why do social movements receive extensive news attention in the mainstream news media? We address this question with an institutional mediation model that argues that news-heightening characteristics of movements and political contexts in combination can bring extensive attention to movements. The internal characteristics of movements include their disruptive capacities, organizational resources, and political orientation. The political contexts include a partisan regime being in power, benefiting from national policies, and being under investigation. We also argue that movements that have achieved prominence in the news are likely to remain prominent, but only under specific conditions. We appraise these arguments across 29 social movements, four national newspapers, and 100 years with negative binomial regression analyses and qualitative comparative analyses (QCA). The results support the model and show that movements have no magic bullet to gain extensive news attention, though Congress may have one through investigations. The arguments and results imply that the influence of movements on institutions depends on the nature of those institutions. The drivers of movement influence over news organizations are not the same as those over political and other institutions.

This research note examines the abilities of a large language model (LLM), ChatGPT, to extract structured data on protest events from media accounts. Based on our analysis of 500 articles on Black Lives Matter protests, after an iterative process of prompt improvement on a training dataset, ChatGPT can produce data comparable to or better than a hand-coding method with an enormous reduction in time and minimal cost. While the technique has limitations, LLMs show promise and deserve further study for their use in protest event analysis.