Morally Motivated Networked Harassment as Normative Reinforcement

Moral outrage and shared moral norms energize networked, coordinated harassment online

Networked, coordinated harassment is done by all kinds of communities, from partisan political groups to fandoms. Though the origins of harassment are not necessarily identity-based, the resulting attacks use race, gender, sexuality, religion, and other attributes as vectors, making it more likely that people with marginalized identities will be harassed in ways that are intersectional/more harmful for individuals with multiple marginalized identities.

The key point is that while harrassers draw from identity-based stereotypes in their attacks, they understand their actions as morally justified and based in the target’s actions, rather than their identity. Marwick offers two examples, “I’m not against Anita Sarkeesian because I’m a misogynist/anti-feminist, but because she’s a scammer/liar,” and “I’m not against the 1619 project/Nikole Hannah Jones b/c I’m racist/my white ID is threatened but because she’s a liar who hates white people and white children.” In these cases, the speaker justifies their harassment of women by defining the woman as immoral and themselves therefore as moral actors for policing their immoral behavior.

Documenting women's contributions to society faces an uphill battle against users' interpretation of Wikipedia's "notability" requirements

Gender is one of the most pervasive and insidious forms of inequality. For example, English-language Wikipedia contains more than 1.5 million biographies about notable writers, inventors, and academics, but less than 19% of these biographies are about women. To try and improve these statistics, activists host “edit-a-thons” to increase the visibility of notable women. While this strategy helps create several biographies previously inexistent, it fails to address a more inconspicuous form of gender exclusion. Drawing on ethnographic observations, interviews, and quantitative analysis of web-scraped metadata, this article demonstrates that biographies about women who meet Wikipedia’s criteria for inclusion are more frequently considered non-notable and nominated for deletion compared to men’s biographies. This disproportionate rate is another dimension of gender inequality previously unexplored by social scientists and provides broader insights into how women’s achievements are (under)valued.

More data is available to researchers than ever before - but undertheorized, ad hoc methodologies make for inconsistent findings

Science rarely proceeds beyond what scientists can observe and measure, and sometimes what can be observed proceeds far ahead of scientific understanding. The twenty-first century offers such a moment in the study of human societies. A vastly larger share of behaviours is observed today than would have been imaginable at the close of the twentieth century. Our interpersonal communication, our movements and many of our everyday actions, are all potentially accessible for scientific research; sometimes through purposive instrumentation for scientific objectives (for example, satellite imagery), but far more often these objectives are, literally, an afterthought (for example, Twitter data streams). Here we evaluate the potential of this massive instrumentation—the creation of techniques for the structured representation and quantification—of human behaviour through the lens of scientific measurement and its principles. In particular, we focus on the question of how we extract scientific meaning from data that often were not created for such purposes. These data present conceptual, computational and ethical challenges that require a rejuvenation of our scientific theories to keep up with the rapidly changing social realities and our capacities to capture them. We require, in other words, new approaches to manage, use and analyse data.