Who Has a Choice?: Survey-Based Predictors of Volitionality in Facebook Use and Non-use

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Patrick Skeba, Devansh Saxena, Shion Guha, and Eric P. S. Baumer. (2021). Who Has a Choice?: Survey-Based Predictors of Volitionality in Facebook Use and Non-use. Proceedings of the ACM on Human-Computer Interaction, GROUP.

Abstract

This paper examines volitionality of Facebook usage, that is, which individuals feel they have a choice about whether or not to use the site. It analyzes data from two large surveys, conducted three years apart. Across the two surveys, a variety of factors impacted whether or not respondents saw their Facebook usage as a matter of their own choice, such as engaging in non-use behaviors, measures of Facebook addiction, a sense of their own agency, and, across both studies, level of education. These results expand on prior literature around technology use and non-use, especially in terms of which populations may feel obligated to use, or be unwillingly prevented from using, social media such as Facebook. Furthermore, they provide potential implications both for future work and for technology policy.

Informational Friction as a Lens for Studying Algorithmic Aspects of Privacy

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Patrick Skeba and Eric P. S. Baumer. (2020). Informational Friction as a Lens for Studying Algorithmic Aspects of Privacy. Proceedings of the ACM on Human-Computer Interaction 4, CSCW.

Abstract

This paper addresses challenges in conceptualizing privacy posed by algorithmic systems that can infer sensitive information from seemingly innocuous data. This type of privacy is of imminent concern due to the rapid adoption of machine learning and artificial intelligence systems in virtually every industry. In this paper, we suggest informational friction, a concept from Floridi’s ethics of information, as a valuable conceptual lens for studying algorithmic aspects of privacy. Informational friction describes the amount of work required for one agent to access or alter the information of another. By focusing on amount of work, rather than the type of information or manner in which it is collected, informational friction can help to explain why automated analyses should raise privacy concerns independently of, and in addition to, those associated with data collection. As a demonstration, this paper analyze law enforcement use of facial recognition, andFacebook’s targeted advertising model using informational friction and demonstrate risks inherent to these systems which are not completely identified in another popular framework, Nissenbaum’s Contextual Integrity.The paper concludes with a discussion of broader implications, both for privacy research and for privacy regulation.

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Methods for Generating Typologies of Non/use

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Devansh Saxena, Patrick Skeba, Shion Guha, and Eric P. S. Baumer. (2020). Methods for Generating Typologies of Non/use. Proceedings of the ACM on Human-Computer Interaction 3, CSCW.

Abstract

Prior studies of technology non-use demonstrate the need for approaches that go beyond a simple binary distinction between users and non-users. This paper proposes a set of two different methods by which researchers can identify types of non/use relevant to the particular sociotechnical settings they are studying. These methods are demonstrated by applying them to survey data about Facebook non/use. The results demonstrate that the different methods proposed here identify fairly comparable types of non/use. They also illustrate how the two methods make different trade offs between the granularity of the resulting typology and the total sample size. The paper also demonstrates how the different typologies resulting from these methods can be used in predictive modeling, allowing for the two methods to corroborate or disconfirm results from one another. The discussion considers implications and applications of these methods, both for research on technology non/use and for studying social computing more broadly.

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All Users are (Not) Created Equal: Predictors Vary for Different Forms of Facebook Non/use

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Eric P. S. Baumer, Patrick Skeba, Shion Guha, and Geri Gay. (2019). All Users are (Not) Created Equal: Predictors Vary for Different Forms of Facebook Non/use. Proceedings of the ACM Human-Computer Interaction 2, CSCW.

Abstract

Relatively little work has empirically examined use and non-use of social technologies as more than a dichotomous binary, despite increasing calls to do so. This paper compares three different forms of non/use that might otherwise fall under the single umbrella of Facebook “user”: (1) those who have a current active account; (2) those who have deactivated their account; and (3) those who have considered deactivating but not actually done so. A subset of respondents (N=256) from a larger, demographically representative sample of internet users completed measures for usage and perceptions of Facebook, Facebook addiction, privacy experiences and behaviors, and demographics. Multinomial logistic regression modeling shows four specific variables as most predictive of a respondent’s type: negative effects from “addictive” use, subjective intensity of Facebook usage, number of Facebook friends, and familiarity with or use of Facebook’s privacy settings. These findings both fill gaps left by, and help resolve conflicting expectations from, prior work. Furthermore, they demonstrate how valuable insights can be gained by disaggregating “users” based on different forms of engagement with a given technology.

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Departing and Returning: Sense of Agency as an Organizing Concept for Understanding Social Media Non/use Transitions

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Eric P. S. Baumer, Rui Sun, and Peter Schaedler. (2018). Departing and Returning: Sense of Agency as an Organizing Concept for Understanding Social Media Non/use Transitions. Proceedings of the ACM: Human-Computer Interaction 1, CSCW: 23:1-23:19.

Abstract

Recent work has identified a variety of motivations for various forms of technology use and non-use. However, less work has closely examined relationships between those motivations and the experiences of transiting among these different forms of use and non-use. This paper fills that gap by conducting a qualitative interview- and diary-based study where participants were asked to deactivate their Facebook account. An abductive analysis suggests participants’ experiences can be organized under the conceptual umbrella of sense of agency, which refers to an individual’s perception that their actions are under their own control. The analysis shows how, across disparate motivations, all participants took actions that increased their own subjective sense of agency, regardless of whether they returned to Facebook or not. The discussion applies this conceptual lens to prior studies of technology use and non-use. Doing so shows how sense of agency may provide an organizing orientation for understanding subjective experiences of use and non-use.

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Socioeconomic Inequalities in the Non/use of Facebook

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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

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.

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.

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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.

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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.

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