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Robert Sprague, An Ontology of Privacy Law Derived from Probabilistic Topic Modeling Applied to Scholarly Works Using Latent Dirichlet Allocation

Robert Sprague, An Ontology of Privacy Law Derived from Probabilistic Topic Modeling Applied to Scholarly Works Using Latent Dirichlet Allocation

PLSC 2013

Workshop draft abstract:

Privacy, being an evolutionary product of social development, has been a human need and desire for millennia. Privacy law scholarship, in contrast, is a relatively recent phenomenon. Of all the privacy-related law review articles published in the history of the United States, for example, over ninety percent were published after 1990—and half that amount in the past decade. Within this recent profusion of scholarship lies a fundamental conundrum: there is no clear definition of privacy; there is not even consensus of what would constitute an adequate definition. Fundamental categories of privacy have been identified and analyzed—e.g., seclusion, intimacy, surveillance, anonymity, control of information. But most calls for privacy arise from context, as well as advancing technologies, meaning the legal system often has difficulty identifying and protecting rights to privacy. Without a coherent construction of privacy principles shared by the community of scholars, the legal system can never explicitly articulate those principles.

This paper will report preliminary results from a research project aimed at identifying fundamental privacy law principles derived from the writings of legal scholars themselves using probabilistic topic modeling, which uses a suite of algorithms to discover hidden thematic structures in large archives of documents. Topic modeling algorithms are statistical methods that analyze the words of texts to discover the themes (topics) that run through them, how those themes are connected to each other, and how they change over time. For example, in Warren’s and Brandeis’s Harvard Law Review article “The Right to Privacy,” the word “property” is identified as the most statistically probable primary topic in the article—which makes sense since Warren and Brandeis were postulating privacy as a form of intangible property right. A latent Dirichlet allocation, which identifies sets of terms that more tightly co-occur, is incorporated into the topic modeling analysis to identify words most closely associated with each identified topic. In “The Right to Privacy,” in addition to identifying “property” as the primary topic, the process also identifies the words “privacy” and “individual” as co-occurring most frequently with the topic “property.” The latent Dirichlet allocation therefore provides insight into the context in which each identified topic occurs.

All published law review articles which cite “The Right to Privacy” (some 3,500 articles) are being converted to plain text. “The Right to Privacy” was selected as the focal point of the document corpus because it is the original published scholarly call for a formal legal right to privacy in the United States; hence, the vast majority of privacy law scholarship cites to it. Probabilistic topic modeling using latent Dirichlet allocation is being applied to the document corpus in time slices to reveal the evolution of fundamental privacy law concepts expressed in the legal literature published from 1890 through 2012. Studies in different disciplines have demonstrated the ability of latent Dirichlet allocation to analyze the rich underlying structures of a particular domain—depicting emerging and sustained trends in a given discourse. The ultimate goal of this project is to identify the fundamental conceptual structure of privacy law in the United States as reflected by over a century of legal scholarly work.

The proposed paper will provide an overview of the topic modeling process using latent Dirichlet allocation to explain and validate the underlying analytical methodology. Preliminary results of applying the statistical modeling to the law scholarship document corpus as of May 2013 will be presented and discussed.

Alessandro Acquisti & Christina Fong, An Experiment in Hiring Discrimination via Online Social Networks

Alessandro Acquisti & Christina Fong, An Experiment in Hiring Discrimination via Online Social Networks

Comment by: Robert Sprague

PLSC 2012

Workshop draft abstract:

Self-report surveys and anecdotal evidence indicate that U.S. firms are using social networking sites to seek information about prospective hires. However, little is known about how the information they find online actually influences firms’ hiring decisions.  We present the design and preliminary results of a series of controlled experiments of the impact that information posted on a popular social networking site by job applicants can have on employers’ hiring behavior. In two studies (a survey experiment and a field experiment) we measure the ratio of callbacks that different job applicants receive as function of their personal traits. The experiments focus on traits that U.S. employers are not allowed to enquiry about during interviews, but which can be inferred from perusing applicants’ online profiles: religious and sexual orientation, and family status.

Lothar Determann and Robert Sprague, Intrusive Monitoring: Employee Privacy Expectations are Reasonable in Europe, Destroyed in the United States

Lothar Determann and Robert Sprague, Intrusive Monitoring: Employee Privacy Expectations are Reasonable in Europe, Destroyed in the United States

Comment by: Vince Polley

PLSC 2011

Workshop draft abstract:

In the increasingly global economy and workplace, the difference in workplace privacy expectations and protections in the United States and Europe stand out.  In the United States, privacy protections depend on whether employees have reasonable privacy expectations, but employers are relatively free to destroy actual expectations through notices.  In Europe, workplace privacy is not conditioned on employee privacy expectations, but is protected as a matter of public policy.  Thus, in Europe – where reasonable privacy expectations are not a condition to privacy protection – employees can actually and reasonably expect workplace privacy, and in the United States – where privacy protections depend on reasonable privacy expectations – employees cannot expect much privacy in practice. Our article will examine the underlying policy reasons and legal frameworks that control the extent to which employers may monitor their employees, including implications for multinational employers and employees in the United States and Europe.