Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them.

Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave - often within seconds - among multiple applications, locations, functions and media. We describe an end-to-end system for capturing and analyzing the "screenome" of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple time scale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory and privacy.

Self-disclosure and social media: motivations, mechanisms and psychological well-being.

Self-disclosure is pervasive on social media and has significant implications for psychological well-being. In this review we synthesize recent research on the motivations, mechanisms and effects of self-disclosure on well-being and then propose a framework that highlights the bidirectional relationship between self-disclosure and well-being. The framework details the mechanisms by which self-disclosure on social media can influence well-being and how self-disclosure fulfills particular needs of individuals with different well-being characteristics. We call for future research to examine the proposed bi-directional relationship, especially studies designed to tease out causal effects.

Effects of Opinion Climate, Efficacy Messages, and Publicness of Social Media on Intentions to Retransmit Anti-Binge Drinking Messages on Facebook.

Reducing the rate of college binge drinking is a major public health goal. Social media sites such as Facebook serve as platforms for young adults' online communication, so they could potentially extend the reach of health campaign messages via retransmission. Thus, it is important to identify the factors that predict intentions to share health-related messages on social media. Drawing on the Spiral of Silence framework, the current research examined the effects of opinion climate, message efficacy, and publicness of social media on message retransmission intentions for anti-binge drinking "how-to" messages-messages that include advice and recommendations that target beliefs about efficacy. A 2 × 2 × 2 (efficacy: high vs. low × opinion climate: support vs. oppose × channel: public vs. private) between-subjects experiment was conducted. Data from 245 participants on Amazon Mechanical Turk demonstrated that people were more willing to share when they had an anti- rather than a pro-binge drinking opinion climate, when the messages were more useful, and when they were asked to share via private messaging rather than via public status updates. Theoretical and practical implications for the psychological mechanisms underlying message retransmission on social media are discussed.

Stereotype Threat in Virtual Learning Environments: Effects of Avatar Gender and Sexist Behavior on Women's Math Learning Outcomes.

Women in math, science, and engineering (MSE) often face stereotype threat: they fear that their performance in MSE will confirm an existing negative stereotype-that women are bad at math-which in turn may impair their learning and performance in math. This research investigated if sexist nonverbal behavior of a male instructor could activate stereotype threat among women in a virtual classroom. In addition, the research examined if learners' avatar representation in virtual reality altered this nonverbal process. Specifically, a 2 (avatar gender: female vs. male) × 2 (instructor behavior: dominant sexist vs. nondominant or nonsexist) between-subjects experiment was used. Data from 76 female college students demonstrated that participants learned less and performed worse when interacting with a sexist male instructor compared with a nonsexist instructor in a virtual classroom. Participants learned and performed equally well when represented by female and male avatars. Our findings extend previous research in physical learning settings, suggesting that dominant-sexist behaviors may give rise to stereotype threat and undermine women's learning outcomes in virtual classrooms. Implications for gender achievement gaps and stereotype threat are discussed.