Social computing experts are gathering in New York City this week for the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). Research from Facebook will be presented in oral paper and poster sessions.
Among this research is the paper The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments (Yuhang Zhao, Shaomei Wu, Lindsay Reynolds and Shiri Azenkot). Visual content plays an increasingly important role in our daily communications online. Like sighted people, people who are visually impaired want to share photographs on social networking services, but find it difficult to identify and select photos from their albums. The research conducted in this paper aims to address this problem by incorporating state-of-the-art computer-generated descriptions into Facebook’s photo-sharing feature. Read more about this research here.
Facebook researchers and engineers will also be organizing and participating in workshops throughout the week. Keep reading to learn more about the research being presented at CSCW.
Characterizing Online Public Discussions Through Patterns of Participant Interactions
Justine Zhang, Cristian Danescu-Niculescu-Mizil, Christy Sauper and Sean Taylor
Public discussions on social media platforms are an intrinsic part of online information consumption. Characterizing the diverse range of discussions which can arise is crucial for these platforms, as they may seek to organize and curate them. This paper introduces a framework to characterize public discussions, relying on a representation that captures a broad set of social patterns which emerge from the interactions between interlocutors, comments, and audience reactions.
We apply our framework to study public discussions on Facebook at two complementary scales. First, at the level of individual discussions, we use it to predict a discussion’s future trajectory, anticipating future antisocial actions (such as participants blocking each other) and forecasting the discussion’s growth. Second, we systematically analyze the variation of discussions across thousands of Facebook sub-communities, revealing subtle differences (and unexpected similarities) in how people interact when discussing online content. We further show that this variation is driven more by participant tendencies than by the content triggering these discussions.
The Effect of Computer-Generated Descriptions on Photo-Sharing Experiences of People with Visual Impairments
Yuhang Zhao, Shaomei Wu, Lindsay Reynolds and Shiri Azenkot
Like sighted people, visually impaired people want to share photographs on social networking services, but find it difficult to identify and select photos from their albums. We aimed to address this problem by incorporating state-of-the-art computer-generated descriptions into Facebook’s photo-sharing feature. We interviewed 12 visually impaired participants to understand their photo-sharing experiences and designed a photo description feature for the Facebook mobile application. We evaluated this feature with six participants in a seven-day diary study. We found that participants used the descriptions to recall and organize their photos, but they hesitated to upload photos without a sighted person’s input. In addition to basic information about photo content, participants wanted to know more details about salient objects and people, and whether the photos reflected their personal aesthetic. We discuss these findings from the lens of self-disclosure and self-presentation theories and propose new computer vision research directions that will better support visual content sharing by visually impaired people.
How Social Ties Influence Hurricane Evacuation Behavior
Danaë Metaxa-Kakavouli, Paige Maasand Daniel P. Aldritch
Natural disasters carry enormous costs every year, both in terms of lives and materials. Evacuation from potentially affected areas stands out among the most critical factors that can reduce mortality and vulnerability to crisis. We know surprisingly little about the factors that drive this important and often life-saving behavior, though recent work has suggested that social capital may play a critical and previously underestimated role in disaster preparedness. Moving beyond retrospective self-reporting and vehicle count estimates, we use social media data to examine connections between levels of social capital and evacuation behavior. This work is the first of its kind, examining these phenomena across three major disasters in the United States—Hurricane Harvey, Hurricane Irma, and Hurricane Maria—using aggregated, de-identified data from over 1.5 million Facebook users. Our analysis confirms that, holding confounding factors constant, several aspects of social capital are correlated with whether or not an individual evacuates. Higher levels of bridging and linking social ties correlate strongly with evacuation. However, these social capital related factors are not significantly associated with the rate of return after evacuation.
Panel: Without a Trace: How Studying Invisible Interactions Can Help Us Understand Social Media
Nicole Ellison, Megan French, Eden Litt, S. Shyam Sundar and Penny Trieu
Workshop: The Changing Contours of “Participation” in Data-driven, Algorithmic Ecosystems: Challenges, Tactics, and an Agenda
Christine T. Wolf, Haiyu Zhu, Julia Bullard, Min Kyung Lee and Jed R. Brubaker