Socioeconomic Inequalities in the Non/use of Facebook

Status

Eric P. S. Baumer (2018). Socioeconomic Inequalities in the Non/use of Facebook. in Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI). (Montréal, QC).

Abstract

Use and non-use of technology can occur in a variety of forms. This paper analyzes data from a probabilistic sample of 1000 US households to identify predictors for four different types of use and non-use of the social media site Facebook. The results make three important contributions. First, they demonstrate that many demographic and socioeconomic predictors of social media use and non-use identified in prior studies hold with a larger, more diverse sample. Second, they show how going beyond a binary distinction between use and non-use reveals inequalities in social media use and non-use not identified in prior work. Third, they contribute to ongoing discussions about the representativeness of social media data by showing which populations are, and are not, represented in samples drawn from social media.

ACM  pre-print

What Would You Do? Design Fiction and Ethics

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Eric P. S. Baumer, Timothy Berrill, Sarah C. Botwinick, Jonathan L. Gonzales, Kevin Ho, Allison Kundrik, Luke Kwon, Tim LaRowe, Chan P. “Sam” Nguyen, Fredy Ramirez, Peter Schaedler, William Ulrich, Amber Wallace, Yuchen Wan, and Benjamin Weinfeld. (2018). What Would You Do? Design Fiction and Ethics. in Proceedings of the ACM Conference on Supporting Group Work (GROUP), Design Fiction Track. (Sanibel Island, FL).

Abstract

Design fiction can be highly effective at envisioning possible futures. That envisioning enables, among other things, considering ethical implications of possible technologies. This paper highlights that capacity through a cu- rated collection of five short design fiction pieces, each accompanied by its own author statement. Spanning multiple genres, each piece highlights ethical issues in its own way. After considering the unique strategies that each piece uses to highlight ethical issues, the paper concludes with considerations of how design fiction can advance broader discussions of ethics in computing.

Regrets, I’ve Had A Few: When Regretful Experiences Do (and Don’t) Compel Users to Leave Facebook

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Shion Guha, Eric P. S. Baumer, and Geri Gay. (2018). Regrets, I’ve Had A Few: When Regretful Experiences Do (and Don’t) Compel Users to Leave Facebook. in Proceedings of the ACM Conference on Supporting Group Work (GROUP). (Sanibel Island, FL).

Abstract

Previous work has explored regretful experiences on social media. In parallel, scholars have examined how people do not use social media. This paper aims to synthesize these two research areas and asks: Do regretful experiences on social media influence people to (consider) not using social media? How might this influence differ for different sorts of regretful experiences? We adopted a mixed methods approach, combining topic modeling, logistic regressions, and contingency analysis to analyze data from a web survey with a demographically representative sample of US internet users (n=515) focusing on their Facebook use. We found that experiences that arise because of users’ own actions influence actual deactivation of their Facebook account, while experiences that arise because of others’ actions lead to considerations of non-use. We discuss the implications of these findings for two theoretical areas of interest in HCI: individual agency in social media use and the networked dimensions of privacy.

Effects of Comment Curation with Opposition on Coherence in Online Policy Discussion

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Brian J. McInnis, Dan Cosley, Eric P. S. Baumer, Gilly Leshed. (2018). Effects of Comment Curation with Opposition on Coherence in Online Policy Discussion. in Proceedings of the ACM Conference on Supporting Group Work (GROUP). (Sanibel Island, FL).

Abstract

Public concern related to a policy may span a range of topics. As a result, policy discussions struggle to deeply examine any one topic before moving to the next. In policy deliberation re- search, this is referred to as a problem of topical coherence. In an experiment, we curated the comments in a policy discussion to prioritize arguments for or against a policy proposal, and examined how this curation and participants’ initial positions of support or opposition to the policy affected the coherence of their contributions to existing topics. We found an asymmetric interaction between participants’ initial positions and comment curation: participants with different initial positions had unequal reactions to curation that foregrounded comments with which they disagreed. This asymmetry implies that the factors underlying coherence are more nuanced than prioritizing participants’ agreement or disagreement. We discuss how this finding relates to curating for coherent disagreement, and for curation more generally in deliberative processes.

Toward Human-Centered Algorithm Design

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Eric P. S. Baumer. (2017). Toward Human-Centered Algorithm Design. Big Data & Society, 4(2).

Abstract

As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.

DOI

Comparing Grounded Theory and Topic Modeling: Extreme Divergence or Unlikely Convergence?

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Eric P. S. Baumer, David Mimno, Shion Guha, Emiy Quan, and Geri Gay. (2017). Comparing Grounded Theory and Topic Modeling: Extreme Divergence or Unlikely Convergence? Journal of the Association for Information Science and Technology (JASIST), 68(6): 1397–1410.

Abstract

Researchers in information science and related areas have developed various methods for analyzing textual data, such as survey responses. This article describes the application of analysis methods from two distinct fields, one method from interpretive social science and one method from statistical machine learning, to the same survey data. The results show that the two analyses produce some similar and some complementary insights about the phenomenon of interest, in this case, nonuse of social media. We compare both the processes of conducting these analyses and the results they produce to derive insights about each method’s unique advantages and drawbacks, as well as the broader roles that these methods play in the respective fields where they are often used. These insights allow us to make more informed decisions about the tradeoffs in choosing different methods for analyzing textual data. Further- more, this comparison suggests ways that such methods might be combined in novel and compelling ways.

DOI

Post-userism

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Eric P. S. Baumer and Jed R. Brubaker. (2017). Post-userism. in Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI). (Denver, CO).

Abstract

HCI is focused on improving the interactions we have with technology and innovating new types of interactions, as well as expanding the types of people for whom those interactions are designed. Central to these efforts is the simultaneously empowering and contested construct of the “user.” This paper examines what the construct of the user highlights, as well as what it conceals. We introduce post- userism, a perspective that simultaneously acknowledges the limits of, and proposes alternatives to, the central construct of the user as proxy for the “human” in HCI. Drawing on developments across the historical trajectory of HCI, we articulate how the user is enacted across four different levels of representation—systems, interface, design process, and the ideology—and identify situations where the user breaks down. Synthesizing prior work, we offer a series of strategies for grappling with such situations. In doing so, we seek to overcome the limitations imposed by the user and develop a language that will aid in evolving the foundations of HCI by asking what, exactly, we place at the center of our scholarship and design.

DOI

When Subjects Interpret the Data: Social Media Non-use as a Case for Adapting the Delphi Method to CSCW

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Eric P. S. Baumer, Xiaotong Xu, Christine Chu, Shion Guha, and Geri K. Gay. (2017). When Subjects Interpret the Data: Social Media Non-use as a Case for Adapting the Delphi Method to CSCW. in Proceedings of the ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW). (Portland, OR).

Abstract

This paper describes the use of the Delphi method as a means of incorporating study participants into the processes of data analysis and interpretation. As a case study, it focuses on perceptions about use and non-use of the social media site Facebook. The work presented here involves three phases. First, a large survey included both a demographically representative sample and a convenience sample. Second, a smaller follow-up survey presented results from that survey back to survey respondents. Third, a series of qualitative member checking interviews with additional survey respondents served to validate the findings of the follow-up survey. This paper demonstrates the utility of Delphi by highlighting the ways that it enables us to synthesize across these three study phases, advancing understanding of perceptions about social media use and non-use. The paper concludes by discussing the broader applicability of the Delphi method across CSCW research.

DOI

Imagined Facebook: An exploratory study of non-users’ perceptions of social media in Rural Zambia

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Susan P. Wyche and Eric P. S. Baumer (2016). Imagined Facebook: An Exploratory Study of Non-Users’ Perceptions of Social Media in Rural Zambia. New Media & Society.

Abstract

This article describes an exploratory study of Facebook non-users living in rural Zambia. Drawing on evidence from 37 group interviews with mobile phone owners, we discovered that the majority of our participants were aware of, or ‘imagined’ Facebook, despite never having seen or used the site. Our analysis of how participants perceive Facebook suggests that they are interested in the communication and income-generating possibilities access to the site may provide, but that barriers prevent them from acting on these interests. This study contributes to social media research by making visible the experiences of a population whose non-use of information and communication technologies (ICTs) results from economic, infrastructural, and linguistic sources, as well as from other, hitherto less-explored areas. We discuss the practical significance of these findings, offer future research suggestions, and comment on what our respondents have not yet imagined about Facebook.

DOI

Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination

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Michael Muller, Shion Guha, Eric P. S. Baumer, David Mimno, and N. Sadat Shami (2016). Machine Learning and Grounded Theory Method: Convergence, Divergence, and Combination. in Proceedings of the ACM Conference on Supporting Group Work (GROUP). (Sanibel Island, FL).

Abstract

Grounded Theory Method (GTM) and Machine Learning (ML) are often considered to be quite different. In this note, we explore unexpected convergences between these methods. We propose new research directions that can further clarify the relationships between these methods, and that can use those relationships to strengthen our ability to describe our phenomena and develop stronger hybrid theories.

DOI