3,470 research outputs found
Reliable online social network data collection
Large quantities of information are shared through online social networks, making them attractive sources of data for social network research. When studying the usage of online social networks, these data may not describe properly users’ behaviours. For instance, the data collected often include content shared by the users only, or content accessible to the researchers, hence obfuscating a large amount of data that would help understanding users’ behaviours and privacy concerns. Moreover, the data collection methods employed in experiments may also have an effect on data reliability when participants self-report inacurrate information or are observed while using a simulated application. Understanding the effects of these collection methods on data reliability is paramount for the study of social networks; for understanding user behaviour; for designing socially-aware applications and services; and for mining data collected from such social networks and applications. This chapter reviews previous research which has looked at social network data collection and user behaviour in these networks. We highlight shortcomings in the methods used in these studies, and introduce our own methodology and user study based on the Experience Sampling Method; we claim our methodology leads to the collection of more reliable data by capturing both those data which are shared and not shared. We conclude with suggestions for collecting and mining data from online social networks.Postprin
E-Commerce Digital Information Transparency and Satisfaction. Can We Have Too Much of a Good Thing?
Despite core product and service quality improvements and advances in shopping processes and technology, customers often report being unsatisfied with their online purchases. One plausible reason for lower customer satisfaction rates is too much or too little information that is shared with the customers about their orders. We show that when forming their perceptions about the purchases, customers form digital information satisfaction (DIS) levels as they evaluate supplementary informational services in addition to the core product being purchased. We believe that DIS is one of the dimensions of overall customer satisfaction. We also show that supplementary informational services are essential in meeting the increased informational needs of online shopping and, thus, can explain the decreased overall customer satisfaction level through the decreases in DIS.
We develop and test the Digital Information Transparency and Satisfaction (DITS) model that shows how supplemental informational services influence digital information satisfaction (DIS_ in e-commerce. By doing so, this dissertation introduces a new dimension of satisfaction in the era of online shopping. This helps close the knowledge gap in the current research on overall customer satisfaction by showing that too much information transparency can harm the overall experience of the customers, thus leading to decreases in DIS. The study results provide a platform for future research on the influence of informational services provided during online shopping. Explaining the role of information shared with the customers in their perceptions of transparency and, consequently, DIS may help provide crucial practical business insights. Thus, by proposing the DITS model, this dissertation brings contributions to both theory and praxis by enhancing the understanding of DIS, which can serve as a robust foundation for future research on decreasing levels of overall customer satisfaction in a digital setting, as well as help companies improve their customer relationships
Disclosure of Personal Information under Risk of Privacy Shocks
Companies are under an increasing pressure by policy makers to publicize data breaches. Such notification obligations require announcing the loss of personal data collected from customers, because of hacker attacks or other incidents. While notification is likely to impact on firms’ reputation, we know little about the impact such notifications have on consumers with respect to disclosure of their personal data. We present the problem as a dynamic lottery with personal data under the risk of privacy shocks and experimentally study how the privacy breach notification changes an individual’s behavior regarding data disclosure. Our results suggest that the notification induces individuals – disregarding the sensitivity of their data – to disclose more
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Remedying Security Concerns at an Internet Scale
The state of security across the Internet is poor, and it has been so since the advent of the modern Internet. While the research community has made tremendous progress over the years in learning how to design and build secure computer systems, network protocols, and algorithms, we are far from a world where we can truly trust the security of deployed Internet systems. In reality, we may never reach such a world. Security concerns continue to be identified at scale through-out the software ecosystem, with thousands of vulnerabilities discovered each year. Meanwhile, attacks have become ever more frequent and consequential.As Internet systems will continue to be inevitably affected by newly found security concerns, the research community must develop more effective ways to remedy these issues. To that end, in this dissertation, we conduct extensive empirical measurements to understand how remediation occurs in practice for Internet systems, and explore methods for spurring improved remediation behavior. This dissertation provides a treatment of the complete remediation life cycle, investigating the creation, dissemination, and deployment of remedies. We start by focusing on security patches that address vulnerabilities, and analyze at scale their creation process, characteristics of the resulting fixes, and how these impact vulnerability remediation. We then investigate and systematize how administrators of Internet systems deploy software updates which patch vulnerabilities across the many machines they manage on behalf of organizations. Finally, we conduct the first systematic exploration of Internet-scale outreach efforts to disseminate information about security concerns and their remedies to system administrators, with an aim of driving their remediation decisions. Our results show that such outreach campaigns can effectively galvanize positive reactions.Improving remediation, particularly at scale, is challenging, as the problem space exhibits many dimensions beyond traditional computer technical considerations, including human, social, organizational, economic, and policy facets. To make meaningful progress, this work uses a diversity of empirical methods, from software data mining to user studies to Internet-wide network measurements, to systematically collect and evaluate large-scale datasets. Ultimately, this dissertation establishes broad empirical grounding on security remediation in practice today, as well as new approaches for improved remediation at an Internet scale
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Supporting Location Privacy Management through Feedback and Control
Participation in modern, socially-focused digital systems involves a large degree of privacy management, i.e. controlling who may access what information under what circumstances. Effective privacy management (control) requires that mobile systems’ users be able to make informed privacy decisions as their experience and knowledge of a system progresses. By informed, we mean users be aware of the actual information flow. Moreover, privacy preferences vary across the context and it is hard to define privacy policy that reflects the dynamic nature of our lives.
This research explores the problem of supporting awareness of information flow and designing usable interfaces for maintaining privacy policies ad-hoc. We borrow from the world of Computer Supported Collaborative Work (CSCW) and propose to incorporate social translucence, a design approach that “supports coherent behaviour by making participants and their activities visible to one another”. We use the characteristics of social translucence, namely visibility, awareness and accountability in order to introduce social norms in spatially dispersed systems. Our research is driven by two questions: (1) how can artifacts from real world social interaction, such as responsibility, be embedded into mobile interaction; and (2) can systems be designed in which both privacy violations and the burden of privacy management is minimized.
The contributions of our work are: (1) an implementation of Buddy Tracker, privacy-aware location-sharing application based on the social translucence; (2) the design and evaluation of the concept of real-time feedback as a means of incorporating social translucence in location-sharing scenarios; and finally (3) a novel interface for ad-hoc privacy management called Privacy-Shake.
We explore the role of real-time feedback for privacy management in the context of Buddy Tracker. Informed by focus group discussions, interviews, surveys and two field trials of Buddy Tracker we found that when using a system that provided real-time feedback, people were more accountable for their actions and reduced the number of unreasonable location requests. From our observations we develop concrete design guidelines for incorporating real-time feedback into information sharing applications in a manner that ensures social acceptance of the technology
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