Cyberwarriors and influence peddlers spread plausible misinformation as a cost-effective way to advance their cause – or just to earn ad revenue. In the run-up to the 2016 elections, Facebook and Twitter performed poorly, amplifying a lot of misinformation. CSMR Faculty Director Paul Resnick writes in The Conversation that their performance looks much different in the 2018 cycle.

A publicly-available dataset of 2,848 Twitter accounts that were flagged as Russian Trolls under the Mueller investigation was used to train a machine learning model. Then we applied the model to select journalists’ Twitter feeds and identified Russian Trolls attempting to influence them. This paper, originally posted on Medium, describes the Center for Social Media Responsibility’s ongoing research in this area.

The Guardian newspaper’s introduction of single-layer hierarchical threading to its comment section creates a natural experiment for CSMR researchers to better understand the consequences of this design change. Consistent with the publisher’s aims, their research shows that the new design was followed by an increase in the rate of individuals returning to post again, both on any given article, and via the commenting service as a whole.

Ceren Budak, University of Michigan
R. Kelly Garrett, Ohio State University
Paul Resnick, University of Michigan
Julia Kamin, University of Michigan

The Guardian—the fifth most widely read online newspaper in the world as of 2014—changed conversations on its commenting platform by altering its design from non-threaded to single-level threaded in 2012. We studied this naturally occurring experiment to investigate the impact of conversation threading on user retention as mediated by several potential changes in conversation structure and style. Our analysis shows that the design change made new users significantly more likely to comment a second time, and that this increased stickiness is due in part to a higher fraction of comments receiving responses after the design change. In mediation analysis, other anticipated mechanisms such as reciprocal exchanges and comment civility did not help to explain users’ decision to return to the commenting system; indeed, civility did not increase after the design change and reciprocity declined. These analyses show that even simple design choices can have a significant impact on news forums’ stickiness. Further, they suggest that this influence is more powerfully shaped by affordances—the new system made responding easier—than by changes in users’ attention to social norms of reciprocity or civility. This has an array of implications for designers.

Proc. ACM Hum.-Comput. Interact. 1, CSCW, Article 27 (November 2017), 20 pages. https://doi.org/10.1145/3134662 

Social Media as Social Transition Machinery

CSMR research into life transitions describes the ways that different Social Media platforms work together to enable people to carry out different types of transition work, while drawing from different types of support networks. To best facilitate online transition work, Social Media platforms should be designed to foster social connectivity while acknowledging the importance of platform separation.

Oliver L. Haimson, University of Michigan School of Information

Social media, and people’s online self-presentations and social networks, add complexity to people’s experiences managing changing identities during life transitions. I use gender transition as a case study to understand how people experience liminality on social media. I qualitatively analyzed data from transition blogs on Tumblr (n=240), a social media blogging site on which people document their gender transitions, and in-depth interviews with transgender bloggers (n=20). I apply ethnographer van Gennep’s liminality framework to a social media context and contribute a new understanding of liminality by arguing that reconstructing one’s online identity during life transitions is a rite of passage. During life transitions, people present multiple identities simultaneously on different social media sites that together comprise what I call social transition machinery. Social transition machinery describes the ways that, for people facing life transitions, multiple social media sites and networks often remain separate, yet work together to facilitate life transitions.

KEYWORDS Social media; social network sites; life transitions; identity transitions; online identity; Tumblr; Facebook; transgender; non-binary; LGBTQ.

PACM Human-Computer Interaction, Vol. 2, No. CSCW, Article 63. Publication date: November 2018. https://doi.org/10.1145/3274332 .

CSMR Advances Algorithm Auditing

 

CSMR faculty member Christian Sandvig is coordinating a cross-university and cross-industry partnership to develop “algorithm audits:” new methods to provide accountability to automated decision-making on social media platforms.

Algorithm auditing is an emerging term of art for a research design that has shown promise in identifying unwanted consequences of automation on social media platforms. Auditing in this sense takes its name from the social scientific “audit study” where one feature is manipulated in a field experiment, although it is also reminiscent of a financial audit. An overview of the area was recently published in Nature.

A CSMR-led multidisciplinary team, described at http://auditingalgorithms.science/ has produced events, reading lists, educational activities, and will publish a white paper that aims to coalesce this new area of inquiry. Based at Michigan, the effort includes the University of Illinois, Harvard University, and participants who have worked at social media and tech companies like Facebook, Google, Microsoft, and IBM. Participants are working to clarify the potential dangers of social media algorithms and to specify these dangers as new research problems. They have presented existing methods for auditing as well as the need for new methods. Ultimately, they hope to define a research agenda that can provide new insights that advance science and benefit society in the area of social media responsibility.

This initiative is sponsored by the National Science Foundation.

9th Annual U-M Social Media Day

UMSI Assistant Professor Florian Schaub on Social Media Privacy and Action: https://twitter.com/UMich/status/1012800331363831808 "Privacy is not just about protecting yourself, it's about protecting your community."

When Online Harassment is Perceived as Justified

CSMR students and faculty presented a paper on online vigilantism and counterbalancing intervention at the Twelfth International AAAI Conference on Web and Social Media. Their research helps platform companies understand and moderate the effects of social conformity and the propensity for retributive justice.
Lindsay Blackwell, University of Michigan School of Information Tianying Chen, University of Michigan School of Information Sarita Schoenebeck, University of Michigan School of Information Cliff Lampe, University of Michigan School of Information Most models of criminal justice seek to identify and punish offenders. However, these models break down in online environments, where offenders can hide behind anonymity and lagging legal systems. As a result, people turn to their own moral codes to sanction perceived offenses. Unfortunately, this vigilante justice is motivated by retribution, often resulting in personal attacks, public shaming, and doxing— behaviors known as online harassment. We conducted two online experiments (n=160; n=432) to test the relationship between retribution and the perception of online harassment as appropriate, justified, and deserved. Study 1 tested attitudes about online harassment when directed toward a woman who has stolen from an elderly couple. Study 2 tested the effects of social conformity and bystander intervention. We find that people believe online harassment is more deserved and more justified—but not more appropriate—when the target has committed some offense. Promisingly, we find that exposure to a bystander intervention reduces this perception. We discuss alternative approaches and designs for responding to harassment online.
Association for the Advancement of Artificial Intelligence (AAAI) International Conference on Web and Social Media, June 27, 2018. https://aaai.org/ocs/index.php/ICWSM/ICWSM18/paper/view/17902

"Genderfluid" or "Attack Helicopter": Responsible HCI Practice with Non-Binary Gender Variation in Online Communities

Researchers at CSMR and Yahoo have developed guidelines and a practical case study in the careful and ethical analysis of gender in Social Media platforms. The authors argue that careful and sensitive study design, analysis and interpretation is an important commitment for the HCI research community.
Samantha Jaroszewski, Yahoo Danielle Lottridge, Yahoo Oliver L. Haimson, University of Michigan School of Information Katie Quehl, Yahoo ABSTRACT - As non-binary genders become increasingly prevalent, researchers face decisions in how to collect, analyze and interpret research participants' genders. We present two case studies on surveys with thousands of respondents, of which hundreds reported gender as something other than simply women or men. First, Tumblr, a blogging platform, resulted in a rich set of gender identities with very few aggressive or resistive responses; the second case study, online Fantasy Football, yielded opposite proportions. By focusing on variation rather than dismissing non-binary responses as noise, we suggest that researchers can better capture gender in a way that 1) addresses gender variation without othering or erasing non-binary respondents; and 2) minimizes "trolls'" opportunity to use surveys as a mischief platform. The analyses of these two distinct case studies find significant gender differences in community dimensions of participation in both networked spaces as well as offering a model for inclusive mixed-methods HCI research. Author Keywords - Survey research; social media; gender; non-binary; transgender; LGBTQ; online communities; trolling; Tumblr; Fantasy sports. ACM Classification Keywords - H.5.3. Information interfaces and presentation (e.g., HCI): Group and Organization Interfaces: Collaborative computing, Computer-supported cooperative work, Web-based interaction.
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. Publication date: April 2018. https://doi.org/10.1145/3173574.3173881 .

Announcing Pregnancy Loss on Facebook: A Decision-Making Framework for Stigmatized Disclosures on Identified Social Network Sites

CSMR researchers have developed a six-factor framework for disclosures of pregnancy loss on Social Media sites (Facebook, e.g.): self-related, audiencerelated, societal, platform and affordance-related, network-level, and temporal. While pregnancy loss was the focus, the framework could be applicable to other sensitive Social Media disclosures.
Nazanin Andalibi Andrea Forte ABSTRACT - Pregnancy loss is a common experience that is often not disclosed in spite of potential disclosure benefits such as social support. To understand how and why people disclose pregnancy loss online, we interviewed 27 women in the U.S. who are social media users and had recently experienced pregnancy loss. We developed a decision-making framework explaining pregnancy loss disclosures on identified social network sites (SNS) such as Facebook. We introduce network-level reciprocal disclosure, a theory of how disclosure reciprocity, usually applied to understand dyadic exchanges, can operate at the level of a social network to inform decision-making about stigmatized disclosures in identified SNSs. We find that 1) anonymous disclosures on other sites help facilitate disclosure on identified sites (e.g., Facebook), and 2) awareness campaigns enable sharing about pregnancy loss for many who would not disclose otherwise. Finally, we discuss conceptual and design implications. CAUTION: This paper includes quotes about pregnancy loss.
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. Publication date: April 2018. https://doi.org/10.1145/3173574.3173732 .

Pseudonymous Parents: Comparing Parenting Roles and Identities on the Mommit and Daddit Subreddits

CSMR researchers explore gender-role conformity and community, with support from the Mozilla Corporation and the National Science Foundation. Their work helps platforms better understand and serve parents seeking peer-support and discussion on issues of discipline, competition, purchases, faith, and online behavior.
Tawfiq Ammari, University of Michigan School of Information Sarita Schoenebeck, University of Michigan School of Information Daniel M. Romero, University of Michigan School of Information ABSTRACT - Gender equality between mothers and fathers is critical for the social and economic wellbeing of children, mothers, and families. Over the past 50 years, gender roles have begun to converge, with mothers doing more work outside of the home and fathers doing more domestic work. However, popular parenting sites in the U.S. continue to be heavily gendered. We explore parenting roles and identities on the platform Reddit.com which is used by both mothers and fathers. We draw on seven years of data from three major parenting subreddits—Parenting, Mommit, and Daddit—to investigate what topics parents discuss on Reddit and how they vary across parenting subreddits. We find some similarities in topics across the three boards, such as sleep training, as well as differences, such as fathers talking about custody cases and Halloween. We discuss the role of pseudonymity for providing parents with a platform to discuss sensitive parenting topics. We conclude by highlighting the benefits of both gender-inclusive and rolespecific parenting boards. This work provides a roadmap for using computational techniques to understand parenting practices online at large scale. Author Keywords Reddit; gender; parenting; anonymity; pseudonymity; social media; language. ACM Classification Keywords H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.
ACM 2018 CHI Conference on Human Factors in Computing Systems, April 21–26, 2018, Montreal, QC, Canada. https://doi.org/10.1145/3173574.3174063 .