Armed groups of civilians known as "self-defense forces" have ousted the powerful Knights Templar drug cartel from several towns in Michoacan. This militia uprising has unfolded on social media, particularly in the "VXM" ("Valor por Michoacan," Spanish for "Courage for Michoacan") Facebook page, gathering more than 170,000 fans. Previous work on the Drug War has documented the use of social media for real-time reports of violent clashes. However, VXM goes one step further by taking on a pro-militia propagandist role, engaging in two-way communication with its audience. This paper presents a descriptive analysis of VXM and its audience. We examined nine months of posts, from VXM's inception until May 2014, totaling 6,000 posts by VXM administrators and more than 108,000 comments from its audience. We describe the main conversation themes, post frequency and relationships with offline events and public figures. We also characterize the behavior of VXM's most active audience members. Our work illustrates VXM's online mobilization strategies, and how its audience takes part in defining the narrative of this armed conflict. We conclude by discussing possible applications of our findings for the design of future communication technologies.
Framing Processes: ways to interpret reality by labeling one's individual experiences within the experiences of society @cite_36 @cite_43 . In social movements, frames represent a set of beliefs and meanings that help to legitimate and motivate the actions of the group. Frames usually emerge by negotiating shared meaning. @cite_36 found that people used social media to crowd-source framing processes, and collectively create an interpretation of street harassment.
@cite_36 @cite_43
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The subconscious influence of framing on perceptions of political issues is well-document in political science and communication research. A related line of work suggests that drawing attention to framing may help reduce such framing effects by enabling frame reflection, critical examination of the framing underlying an issue. However, definite guidance on how to identify framing does not exist. This paper presents a technique for identifying frame-invoking language. The paper first describes a human subjects pilot study that explores how individuals identify framing and informs the design of our technique. The paper then describes our data collection and annotation approach. Results show that the best performing classifiers achieve performance comparable to that of human annotators, and they indicate which aspects of language most pertain to framing. Both technical and theoretical implications are discussed. Framing is a sophisticated form of discourse in which the speaker tries to induce a cognitive bias through consistent linkage between a topic and a specific context (frame). We build on political science and communication theory and use probabilistic topic models combined with time series regression analysis (autoregressive distributed-lag models) to gain insights about the language dynamics in the political processes. Processing four years of public statements issued by members of the U.S. Congress, our results provide a glimpse into the complex dynamic processes of framing, attention shifts and agenda setting, commonly known as ‘spin’. We further provide new evidence for the divergence in party discipline in U.S. politics. CSCW systems are playing an increasing role in activism. How can new communications technologies support social movements? The possibilities are intriguing, but as yet not fully understood. One key technique traditionally leveraged by social movements is storytelling. In this paper, we examine the use of collective storytelling online in the context of a social movement organization called Hollaback, an organization working to stop street harassment. Can sharing a story of experienced harassment really make a difference to an individual or a community? Using Emancipatory Action Research and qualitative methods, we interviewed people who contributed stories of harassment online. We found that sharing stories shifted participants' cognitive and emotional orientation towards their experience. The theory of "framing" from social movement research explains the surprising power of this experience for Hollaback participants. We contribute a way of looking at activism online using social movement theory. Our work illustrates that technology can help crowd-sourced framing processes that have traditionally been done by social movement organizations. This paper presents a principled framework for analyzing collective activities at different levels of semantic granularity from videos. Our framework is capable of jointly tracking multiple individuals, recognizing activities performed by individuals in isolation (i.e., atomic activities such as walking or standing), recognizing the interactions between pairs of individuals (i.e., interaction activities) as well as understanding the activities of group of individuals (i.e., collective activities). A key property of our work is that it can coherently combine bottom-up information stemming from detections or fragments of tracks (or tracklets) with top-down evidence. Top-down evidence is provided by a newly proposed descriptor that captures the coherent behavior of groups of individuals in a spatial-temporal neighborhood of the sequence. Top-down evidence provides contextual information for establishing accurate associations between detections or tracklets across frames and, thus, for obtaining more robust tracking results. Bottom-up evidence percolates upwards so as to automatically infer collective activity labels. Experimental results on two challenging data sets demonstrate our theoretical claims and indicate that our model achieves enhances tracking results and the best collective classification results to date.