Critical and Ethical Studies of Digital and Social Media Minitrack

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The minitrack focuses on two themes: a) studies that critically interrogate the role of DSM in supporting existing power structures or realigning power for underrepresented or social marginalized groups, and b) studies that raise awareness or illustrate the ethical issues associated with doing research on DSM. Examples of the first theme would include the perpetuation of gender-based hostility and bullying found in a range of online environments; the values embedded in the algorithms in platform content management; the political economies and labor conditions of paid and unpaid user-generated content creation; representations and practices of gaming communities and virtual worlds; and individual and collective challenges to established societal institutions (e.g., the Snowden case). Examples of the second theme include the ethical pitfalls involved in studying the flow of misinformation during crisis events (e.g., the Boston Marathon bombing); the challenges and opportunities of studying proprietary DSM data generated in industry settings; and the inferences researchers might make when combining data from multiple DSM platforms (e.g., Twitter with tweet metadata, Facebook, Foursquare).

The minitrack seeks both conceptual and empirical approaches to the theme. Conceptual papers would address foundational theories of critical studies of media or ethical conduct in periods of rapid change—e.g., new metaphors for thinking about information exchange in communities and societies. Empirical papers would draw on studies of social media data that illustrate the critical or ethical dimensions of the use of such data.


Minitrack Co-Chairs:

Tarleton Gillespie (Primary Contact)
Cornell University and Microsoft Research
Email: tlg28@cornell.edu

Mary Gray
Indiana University and Microsoft Research
Email: mlg@microsoft.com

Robert Mason
University of Washington
Email: rmmason@uw.edu

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Recent Submissions

Now showing 1 - 5 of 7
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    The Political Economy of New Media Revisited
    ( 2017-01-04) Van Couvering, Elizabeth
    This paper defines media platforms in terms of the theory of traditional two-sided media markets, then goes on to develop the theory to include content providers as a third side of the market (the “platformisation of media”), the widespread introduction of sellable meta-information about the platform network (the “mediatisation of platforms”), and the importance of social networking technologies to the media platform. Issues of concern raised by this include privacy, intellectual property, and equity. Genres of resistance to unwanted visibility and invisibility, such as spoofing, spamming, fingering and silencing are also noted.
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    Managing Online Trolling: From Deviant to Social and Political Trolls
    ( 2017-01-04) Sanfilippo, Madelyn Rose ; Yang, Shengnan ; Fichman, Pnina
    Trolling behaviors are extremely diverse, varying \ by context, tactics, motivations, and impact. \ Definitions, perceptions of, and reactions to online \ trolling behaviors vary. Since not all trolling is equal \ or deviant, managing these behaviors requires context \ sensitive strategies. This paper describes appropriate \ responses to various acts of trolling in context, based \ on perceptions of college students in North America. In \ addition to strategies for dealing with deviant trolling, \ this paper illustrates the complexity of dealing with \ socially and politically motivated trolling.
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    Keeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media Images
    ( 2017-01-04) Bechmann, Anja
    This paper wants to supplement computational tests of deep learning vision algorithms with a sociologically grounded performance test of three widely used vision algorithms on Facebook images (Clarifai, Google Vision and Inception-v3). \ \ The test shows poor results and the paper suggests the use of a two-level labeling model that combines features with theoretically inspired accounts of the social value of pictures for uploaders. The paper contributes a suggestion for labeling categories that connects the two levels, and in conclusion discusses both advantages and disadvantages in accelerating user profiling through a better understanding of the incentives to upload images in the data-driven algorithmic society.
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    Incidental News: How Young People Consume News on Social Media
    ( 2017-01-04) Boczkowski, Pablo ; Mitchelstein, Eugenia ; Matassi, Mora
    This paper examines the dynamics of news consumption on social media through sixteen open-ended interviews with young users from Argentina. It adopts a texto-material perspective to explore the role of technology and users’ motivations, actions and interpretations. The interviews reveal that the ideal-typical mode in which young users consume news on social media can be characterized with the notion of “incidental news”: most young users get the news on their mobile devices as part of their constant connection to media platforms; they encounter the news all the time, rather than looking for it; but click on them only sporadically and spend little time engaging with the content. Thus, the news becomes un-differentiated from the rest of the social and entertainment information. This mode of news access marks a significant discontinuity with the consumption of news on other media. It also raises major editorial and political implications.
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    HIV Risk on Twitter: the Ethical Dimension of Social Media Evidence-based Prevention for Vulnerable Populations
    ( 2017-01-04) Weibel, Nadir ; Desai, Purvi ; Saul, Lawrence ; Gupta, Amarnath ; Little, Susan
    As of 2016 the HIV/AIDS epidemics is still a key public health problem. Recent reports showed that alarmingly high numbers of people in vulnerable populations are not reached by preventative efforts. Despite technology improvement, we are not yet able to identify populations that are most susceptible to HIV infections. In order to enable evidence-based prevention, we are studying new methods to identify HIV at-risk populations, exploiting Twitter posts as possible indicators of HIV risk. Our research on social network analysis and machine learning outlined the feasibility of using tweets as monitoring tool for HIV-related risk at the demographic, geographical, and social network level. However, this approach highlights ethical dilemmas in three different areas: data collection and analysis, risk inference through imperfect probabilistic approaches, and data-driven prevention. We contribute a description, analysis and discussion of ethics based on our 2-year experience with clinicians, IRBs, and local HIV communities in San Diego, California.