Teresa Scassa - Blog

In October 2016, the data analytics company Geofeedia made headlines when the California chapter of the American Civil Liberties Union (ACLU) issued the results of a major study which sought to determine the extent to which police services in California were using social media data analytics. These analytics were based upon geo-referenced information posted by ordinary individuals to social media websites such as Twitter and Facebook. Information of this kind is treated as “public” in the United States because it is freely contributed by users to a public forum. Nevertheless, the use of social media data analytics by police raises important civil liberties and privacy questions. In some cases, users may not be aware that their tweets or posts contain additional meta data including geolocation information. In all cases, the power of data analytics permits rapid cross-referencing of data from multiple sources, permitting the construction of profiles that go well beyond the information contributed in single posts.

The extent to which social media data analytics are used by police services is difficult to assess because there is often inadequate transparency both about the actual use of such services and the purposes for which they are used. Through a laborious process of filing freedom of information requests the ACLU sought to find out which police services were contracting for social media data analytics. The results of their study showed widespread use. What they found in the case of Geofeedia went further. Although Geofeedia was not the only data analytics company to mine social media data and to market its services to government authorities, its representatives had engaged in email exchanges with police about their services. In these emails, company employees used two recent sets of protests against police as examples of the usefulness of social media data analytics. These protests were those that followed the death in police custody of Freddie Gray, a young African-American man who had been arrested in Baltimore, and the shooting death by police of Michael Brown, an eighteen-year-old African-American man in Ferguson, Missouri. By explicitly offering services that could be used to monitor those who protested police violence against African Americans, the Geofeedia emails aggravated a climate of mistrust and division, and confirmed a belief held by many that authorities were using surveillance and profiling to target racialized communities.

In a new paper, just published in the online, open-access journal SCRIPTed, I use the story around the discovery of Geofeedia’s activities and the backlash that followed to frame a broader discussion of police use of social media data analytics. Although this paper began as an exploration of the privacy issues raised by the state’s use of social media data analytics, it shifted into a paper about transparency. Clearly, privacy issues – as well as other civil liberties questions – remain of fundamental importance. Yet, the reality is that without adequate transparency there simply is no easy way to determine whether police are relying on social media data analytics, on what scale and for what purposes. This lack of transparency makes it difficult to hold anyone to account. The ACLU’s work to document the problem in California was painstaking and time consuming, as was a similar effort by the Brennan Center for Justice, also discussed in this paper. And, while the Geofeedia case provided an important example of the real problems that underlie such practices, it only came to light because Geofeedia’s employees made certain representations by email instead of in person or over the phone. A company need only direct that email not be used for these kinds of communications for the content of these communications to disappear from public view.

My paper examines the use of social media data analytics by police services, and then considers a range of different transparency issues. I explore some of the challenges to transparency that may flow from the way in which social media data analytics are described or characterized by police services. I then consider transparency from several different perspectives. In the first place I look at transparency in terms of developing explicit policies regarding social media data analytics. These policies are not just for police, but also for social media platforms and the developers that use their data. I then consider transparency as a form of oversight. I look at the ways in which greater transparency can cast light on the activities of the providers and users of social media data and data analytics. Finally, I consider the need for greater transparency around the monitoring of compliance with policies (those governing police or developers) and the enforcement of these policies.

A full text of my paper is available here under a CC Licence.

Published in Privacy

The social sciences research community has been buzzing over the announcement on May 17, 2016 that the Social Sciences Research Network (SSRN) has been acquired by Elsevier Publishing Group.

SSRN is a digital repository that was created in order to enable researchers in the social sciences to share their work in advance of its publication. Prior to the launch of SSRN, long delays between submission and print publication of papers had been a significant problem for researchers – particularly those working in rapidly changing and evolving fields. In addition, it was not always easy to find out who was working in similar areas or to be aware of developing trends in research as a result of the long publication delays. SSRN allows researchers to publish working papers, conference papers, and pre-print versions of accepted papers – as well as (where permitted by journals) published versions of papers. Access to the database is free to anyone with an Internet connection. This too is important for sharing academic research more broadly – many published academic journals sit behind digital paywalls making broader public access impractical or impossible. SSRN has been a game-changer, and it is now widely used by academics around the world as a vehicle for sharing research.

Elsevier is a commercial publisher which has, in the past, focused primarily on the fields of science, technology and health. It publishes over 2000 international journals. In recent years it has developed other information “solutions”. These include not only digital publishing platforms, but also data analytics, as well as tools to enhance and facilitate collaboration among researchers.

The controversy over the acquisition of SSRN lies in the deep distrust many researchers seem to have about the willingness of a commercial publisher known for its top-dollar subscriptions and generally restrictive access policies to maintain a publicly accessible information dissemination service that is free to both academics and the broader public. The founders of SSRN maintain that Elsevier, which also publishes open access journals, understands the need for broad sharing of research and has no intention of placing the site behind a paywall. They argue that SSRN’s acquisition by Elsevier will only enhance the services it can offer to scholars.

Critics of the sale of SSRN to Elsevier raise a number of concerns. One of these is, of course, whether SSRN will genuinely continue to be available as a free resource for sharing research. The reassurances of both Elsevier and SSRN’s founders are firm in this respect. Nevertheless, there are concerns that Elsevier might more strictly police what content is available on SSRN. It is likely the case that some academics post articles to which their publishers hold the copyright on the view that enough time has passed since publication to make free dissemination normatively if not legally acceptable.

The potential that access to some content might be limited is only one of the issues that should be on scholars’ radar – and it is probably not the most important one. By acquiring SSRN, Elsevier will enhance its expanding analytics capability – and data analytics are an important part of its business model. Researchers should consider the nature and extent of these analytics and how they might impact on the publication, dissemination, valuation and support for research in other venues and other contexts. For example, how might granting agencies or governments use proprietary data analytics to make decisions about what research to fund or not fund? Will universities purchase data from Elsevier to use in the evaluation of their researchers for tenure, promotion, or other purposes? Does it serve the academic committee to have so much data – and its analytic potential – in the hands of a single private sector organization? Given that this data might have important ramifications for scholars, and, by extension, for society, are there any governance, accountability or oversight mechanisms that will provide insight into how the data is collected or analyzed?

Essentially, the noble project that was SSRN has evolved into a kind of Facebook for academics. Researchers post their articles and conference papers to share with the broader community – and will continue to do so. While for researchers these works are what define them and are the “value” that they contribute to the site, the real commercial value lies in the data that can be mined from SSRN. Who collaborates with whom? How many times is a paper read or downloaded? Who cites whom, and how often? The commercialization of SSRN should be of concern to academics, but it is data governance and not copyright that should be the focus of attention.

Published in Copyright Law

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