6,224 research outputs found

    Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail

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    Developers of pricing strategies in e-commerce businesses see a wide range of opportunities for deploying online price discrimination techniques given their ability to track consumers’ online identity and behavior. In theory, an increasing use of personal data enables organizations to show every single consumer their own personalized price, which is determined by the consumer’s characteristics, e.g. age, gender, surfing history, or location. This paper aims to explore the existence of online price discrimination activities within the German ecommerce market using a three-method approach. First, inquiring the online retailers via email and investigating their public documents; second, surveying students; and third, using a software crawler to simulate surfing activity. Our results do not provide any evidence of individualized price discrimination, which, we argue, is due to economic and political reasons, not technical reasons

    State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

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    Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work

    Honesty is the Best Policy: On the Accuracy of Apple Privacy Labels Compared to Apps' Privacy Policies

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    Apple introduced \textit{privacy labels} in Dec. 2020 as a way for developers to report the privacy behaviors of their apps. While Apple does not validate labels, they do also require developers to provide a privacy policy, which offers an important comparison point. In this paper, we applied the NLP framework of Polisis to extract features of the privacy policy for 515,920 apps on the iOS App Store comparing the output to the privacy labels. We identify discrepancies between the policies and the labels, particularly as it relates to data collected that is linked to users. We find that 287±196\pm196K apps' privacy policies may indicate data collection that is linked to users than what is reported in the privacy labels. More alarming, a large number of (97±30\pm30\%) of the apps that have {\em Data Not Collected} privacy label have a privacy policy that indicates otherwise. We provide insights into potential sources for discrepancies, including the use of templates and confusion around Apple's definitions and requirements. These results suggest that there is still significant work to be done to help developers more accurately labeling their apps. Incorporating a Polisis-like system as a first-order check can help improve the current state and better inform developers when there are possible misapplication of privacy labels

    Systematic Analysis and Visualization of Privacy Policies of Online Services

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    Beyond Compliance

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    Privacy is governed by an array of laws in the United States, and this paper examines one facet of privacy regulation: the privacy of students’ academic records. The Family Educational Rights and Privacy Act (FERPA) protects the privacy of these records, but how do students understand their rights under FERPA, especially with the development of big data and learning analytics technologies that demand unprecedented sharing of student data? This paper begins to answer that question by examining existing literature on privacy in general and with regards to FERPA specifically. It suggests that FERPA places most of the power in controlling student data in the hands of educational institutions but is ultimately unable to address many legal and ethical concerns around current uses of student data. FERPA\u27s ineffectiveness makes it imperative that students understand their rights and are able to protect their own privacy, yet many students are probably not fully aware of their rights and privileges under FERPA. However, further empirical research is needed to explore exactly how students understand their FERPA rights and the implications of student perceptions of academic privacy
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