Friday, February 8, 2:15 - 3:30 PM | Oregon Ballroom 201
Human behavior increasingly takes place in virtual spaces. This session examines how different predictors of people’s behavior – ranging from their personality and identities to their social emotions and motivations – manifest in online settings and affect diverse aspects of behavior, from relationships to information processing and transmission.
Sang Eun Woo
John T. Jost
Nicole B. Ellison
Sang Eun Woo, Purdue University
While we know a lot about how personality is behaviorally expressed off-line, much less is known about the process in online contexts. I will begin by summarizing key findings from a recent study using MyPersonality data collected from a large sample of Facebook users (N =115,873). In this study, we investigated the role of openness and extraversion in predicting socio-informational behaviors on social media. Data suggested that those high in both openness and extraversion are more likely to engage in certain behaviors on Facebook (e.g., “liking” thing, listing events), and tend to use expressive and active social language in their postings. Building from this, I will discuss some big-picture methodological and theoretical questions for further consideration: 1) how is on-line personality different from off-line personality?; 2) how is one’s personality expressed and communicated online?; and 3) what are the key situational factors (i.e., facilitators and constraints) in these processes?
John T. Jost, New York University
Consistent with the theory of political ideology as motivated social cognition, research on social media usage reveals meaningful differences between liberals and conservatives with respect to the structure and function of online social networks; the moral and emotional contents of messages spread; and the likelihood of transmitting rumors and misinformation. In an analysis of Twitter messages concerning the Boston Marathon bombing, my colleagues and I have investigated how and why rumors persist even after the introduction of corrective information (Guess et al., 2018). We observed that conservative Twitter users continued to spread false information about a Saudi attacker after it was debunked, and both liberal and conservative users returned to a “false flag” rumor. The ideological asymmetries we have observed in social media usage are consistent with differences between liberals and conservatives in terms of epistemic motivation, cognitive-motivational style, and conspiratorial thinking (van der Linden et al., 2018).
Molly Crockett, Yale University
Humans reliably respond to insult and injury with moral outrage and costly punishment behavior. This behavior evolved in the context of small foraging groups, but is now widespread in massive online networks. A theory of digital outrage, drawing on principles of reinforcement learning, posits that moral outrage is elicited by stimuli appraised as signifying moral norm violations, and triggers behavioral responses such as gossip, shaming or punishment. Expressing outrage can lead to positive and negative outcomes for oneself and for society. The theory predicts that digital media promotes the expression of outrage by magnifying its stimuli and lowering the threshold for responses. Digital contexts may amplify the personal benefits of outrage but reduce its social benefits. Evidence that supports and challenges the theory will be reviewed and discussed.
Nicole B. Ellison, School of Information, University of Michigan
Attention is a valuable commodity in contemporary media environments, and signaling attention to specific social connections via social media is a form of social grooming that can help strengthen relationships. In this talk I will describe a stream of empirical work that investigates the social implications of user practices related to attention and relationship maintenance, as shaped by the affordances of ephemerality, persistence, and broadcasting. First, I’ll describe a study that examined how Snapchat interactions are perceived by college students and some of the practices associated with why snaps were broadly experienced as positive, supportive, and enjoyable. I will then describe work that explores how Facebook users request help from their networks and a new project that seeks to better understand the relationship between clicking and attention practices in Facebook using a combination of eye-tracking, interview, and survey data.
Saturday, February 9, 2:15 - 3:30 PM | Oregon Ballroom 201
Implicit bias training has received substantial attention as a solution to racial bias, but what is the state of the science surrounding implicit bias training? This invited session will consider evidence for the efficacy of such trainings, alternative approaches to reducing disparities, and applications in the judicial system and beyond.
Neil Lewis, Jr.
Patricia Devine, University of Wisconsin - Madison
Recent decades have witnessed an explosion of work on implicit bias, a term that encompasses the automatic components of prejudice and stereotyping. Key questions focus on the pervasiveness of implicit biases, when and how they are manifested, and how to reduce them. Addressing these issues however, depends on how the construct of implicit bias is measured. The various manifestations of implicit bias outside the laboratory (e.g., reduced eye contact) are often labor-intensive and difficult to reliably produce in lab settings. As such, many researchers rely on easily collected reaction time tasks as proxy measures of implicit bias. Although useful for investigating some questions, the over-reliance on reaction time measures has led to reduced attention to the real-world dilemma faced by people with strong egalitarian values who are vulnerable to the expression of habitual forms of bias, and the distinction between activation and application of biases. I will discuss what is required to effect long-term change, the importance of assessing a broader set of outcomes, and research revealing the effectiveness of an intervention derived from the Prejudice Habit-Breaking Model.
Neil Lewis, Jr., Cornell University
During the 2016 US Presidential Campaign, Candidate Hillary Clinton said “I think implicit bias is a problem for everyone, not just the police… I think, unfortunately, too many of us in America jump to conclusions about each other.” This statement, I believe, led to implicit bias becoming our recent default explanation for all manner of injustices and disparities observed in (American) society. Now there is nothing inherently wrong with the statement – implicit bias surely plays some role in social disparities. The response to this notion, however, is somewhat concerning. When new bias events occur, the lay assumption seems to be that implicit bias trainings are the solution for reducing disparities. At this point, there is limited evidence to support this view, and in fact there is evidence for perhaps even more effective solutions. My remarks will focus on these alternative approaches to reducing biased behaviors.
Erin Cooley, Colgate University
Implicit bias can contribute to discrimination. Yet it is unclear how actively thinking about one’s own implicit biases affects the subsequent expression of overt bias. In the present work, we propose that introspecting about one’s own implicit biases may have diverging effects based on 1) the types of thoughts people have about that bias (i.e., is it my own?) and 2) people’s motivations to respond without prejudice. Across several studies, we demonstrate that taking ownership for one’s implicit biases can either lead to the amplification or the reduction of overt bias—depending on the target of implicit biases (i.e., race versus sexual orientation) as well as people’s internal motivations to respond without prejudice. We conclude that taking ownership of implicit bias is not enough to promote racial equality—people must also be motivated to mitigate that bias.
Calvin Lai, Washington University in St. Louis
Asking whether implicit bias training “works” is as misguided as asking whether teaching math “works”. This is because the answer will depend entirely on how they are taught. As with regular teaching, implicit bias training varies greatly in approach, content, teacher expertise, use of effective teaching techniques, and learning goals. Some trainings involve little more than a series of narrated PowerPoint slides. Other trainings involve expert instructors who hold small, intensive workshops that can last for days. Re-conceptualizing implicit bias training as just another form of teaching opens up new avenues for developing best practices and metrics for assessing learning outcomes.
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