108,012 research outputs found

    Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

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    Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

    The Effects of the Quantification of Faculty Productivity: Perspectives from the Design Science Research Community

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    In recent years, efforts to assess faculty research productivity have focused more on the measurable quantification of academic outcomes. For benchmarking academic performance, researchers have developed different ranking and rating lists that define so-called high-quality research. While many scholars in IS consider lists such as the Senior Scholar’s basket (SSB) to provide good guidance, others who belong to less-mainstream groups in the IS discipline could perceive these lists as constraining. Thus, we analyzed the perceived impact of the SSB on information systems (IS) academics working in design science research (DSR) and, in particular, how it has affected their research behavior. We found the DSR community felt a strong normative influence from the SSB. We conducted a content analysis of the SSB and found evidence that some of its journals have come to accept DSR more. We note the emergence of papers in the SSB that outline the role of theory in DSR and describe DSR methodologies, which indicates that the DSR community has rallied to describe what to expect from a DSR manuscript to the broader IS community and to guide the DSR community on how to organize papers for publication in the SSB

    Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

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    Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

    Amplifying Quiet Voices: Challenges and Opportunities for Participatory Design at an Urban Scale

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    Many Smart City projects are beginning to consider the role of citizens. However, current methods for engaging urban populations in participatory design activities are somewhat limited. In this paper, we describe an approach taken to empower socially disadvantaged citizens, using a variety of both social and technological tools, in a smart city project. Through analysing the nature of citizens’ concerns and proposed solutions, we explore the benefits of our approach, arguing that engaging citizens can uncover hyper-local concerns that provide a foundation for finding solutions to address citizen concerns. By reflecting on our approach, we identify four key challenges to utilising participatory design at an urban scale; balancing scale with the personal, who has control of the process, who is participating and integrating citizen-led work with local authorities. By addressing these challenges, we will be able to truly engage citizens as collaborators in co-designing their city

    Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling

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    Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots. Leveraging such characterization, we design the Social Fingerprinting technique, which is able to discriminate among spambots and genuine accounts in both a supervised and an unsupervised fashion. We finally evaluate the effectiveness of Social Fingerprinting and we compare it with three state-of-the-art detection algorithms. Among the peculiarities of our approach is the possibility to apply off-the-shelf DNA analysis techniques to study online users behaviors and to efficiently rely on a limited number of lightweight account characteristics
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