American Sociological Association

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  1. Preventing Violence: Insights from Micro-Sociology

    Micro-sociology of violence looks at what happens in situations where people directly threaten violence, but only sometimes carry it out. This process and its turning points have become easier to see in the current era of visual data: cell-phone videos, long-distance telephoto lenses, CCTV cameras. New cues and instruments are on the horizon as we look at emotional signals, body rhythms, and monitors for body signs such as heart rate (a proxy for adrenaline level).
  2. CASM: A Deep-Learning Approach for Identifying Collective Action Events with Text and Image Data from Social Media

    Protest event analysis is an important method for the study of collective action and social movements and typically draws on traditional media reports as the data source. We introduce collective action from social media (CASM)—a system that uses convolutional neural networks on image data and recurrent neural networks with long short-term memory on text data in a two-stage classifier to identify social media posts about offline collective action. We implement CASM on Chinese social media data and identify more than 100,000 collective action events from 2010 to 2017 (CASM-China).
  3. Collective Social Identity: Synthesizing Identity Theory and Social Identity Theory Using Digital Data

    Identity theory (IT) and social identity theory (SIT) are eminent research programs from sociology and psychology, respectively. We test collective identity as a point of convergence between the two programs. Collective identity is a subtheory of SIT that pertains to activist identification. Collective identity maps closely onto identity theory’s group/social identity, which refers to identification with socially situated identity categories. We propose conceptualizing collective identity as a type of group/social identity, integrating activist collectives into the identity theory model.
  4. Trouble in Tech Paradise

    The structures of the tech industry, with its dependence on highly skilled immigrant workers, and the H-1B visa, with its dependence on sponsoring companies, bind tech workers in a cycle of legal violence.

  5. Are Robots Stealing Our Jobs?

    The media and popular business press often invoke narratives that reflect widespread anxiety that robots may be rendering humans obsolete in the workplace. However, upon closer examination, many argue that automation, including robotics and artificial intelligence, is spreading unevenly throughout the labor market, such that middle-skill occupations that do not require a college degree are more likely to be affected adversely because they are easier to automate than high-skill occupations.

  6. Who Counts as a Notable Sociologist on Wikipedia? Gender, Race, and the “Professor Test”

    This paper documents and estimates the extent of underrepresentation of women and people of color on the pages of Wikipedia devoted to contemporary American sociologists. In contrast to the demographic diversity of the discipline, sociologists represented on Wikipedia are largely white men. The gender and racial/ethnic gaps in likelihood of representation have exhibited little change over time. Using novel data, we estimate the “risk” of having a Wikipedia page for a sample of contemporary sociologists.
  7. Visualizing Stochastic Actor-based Model Microsteps

    This visualization provides a dynamic representation of the microsteps involved in modeling network and behavior change with a stochastic actor-based model. This video illustrates how (1) observed time is broken up into a series of simulated microsteps and (2) these microsteps serve as the opportunity for actors to change their network ties or behavior. The example model comes from a widely used tutorial, and we provide code to allow for adapting the visualization to one’s own model.

  8. Response to Morgan: On the Role of Status Threat and Material Interests in the 2016 Election

    I am delighted to have the opportunity to respond to Morgan’s article, which is a critique of my recent publication (Mutz 2018). I will restrict my response to matters concerning the data and analysis, excluding issues such as whether the journal PNAS is appropriately named (Morgan this issue:3) as well as Morgan’s views about how this work was covered in various media outlets (Morgan this issue:3–6). These issues are less important than whether material self-interest or status threat motivated Trump supporters.

  9. Text Analysis with JSTOR Archives

    I provide a visual representation of keyword trends and authorship for two flagship sociology journals using data from JSTOR’s Data for Research repository. While text data have accompanied the digital spread of information, it remains inaccessible to researchers unfamiliar with the required preprocessing. The visualization and accompanying code encourage widespread use of this source of data in the social sciences.

  10. Featured Essay: Lost and Saved . . . Again: The Moral Panic about the Loss of Community Takes Hold of Social Media

    Why does every generation believe that relationships were stronger and community better in the recent past? Lamenting about the loss of community, based on a selective perception of the present and an idealization of ‘‘traditional community,’’ dims awareness of powerful inequalities and cleavages that have always pervaded human society and favors deterministic models over a nuanced understanding of how network affordances contribute to different outcomes. Taylor Dotson’s (2017) recent book proposes a broader timeline for the demise of community.