41 research outputs found

    Online social network data as sociometric markers

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    Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics and depth of information, a detailed and accessible account of the challenges associated with data management and data storage is provided. In particular, the general non-anonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, it can be shown that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology

    When 'friends' collide: social heterogeneity and user vulnerability on social network sites

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    The present study examines how the use of social network sites (SNS) increases the potential of experiencing psychological, reputational and physical vulnerability online. From our theoretical perspective, concerns over the use of social network sites and online vulnerability stem from the ease with which users can amass large and diverse sets of online social connections and the associated maintenance costs . To date most studies of online vulnerability have relied on self -rep ort measures, rarely combining such information with user’s validated digital characteristics. Here, f or a stratified sample of 177 UK-based Facebook users aged 1 3 to 77, digitally derived network data , coded for content and subjected to structural analysis, were integrated with self -report measures of social network heterogeneity and user vulnerability. Findings indicated a positive association between Facebook network size and online vulnerability mediated by both social diversity and structural features of the network . In particular, network clustering and the number of non- person contacts were predictive of vulnerability. Our findings support the notion that connecting to large networks of online ‘friends’ can lead to increasingly complex online socialising that is no longer controllable at a desirable level

    Rethinking the digital divide: impacts of student-tutor relationships

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    This article emerged from a series of debates and workshops on the impact of the Digital Divide on educational practice at the ‘Futures of Learning: New Learning Paradigms Conference’ in Paris. The conceptualisation of the Digital Divide into the ‘haves’ and the ‘have-nots’, with a perception of the economically developed world as ‘high tech’ and the developing and underdeveloped worlds as ‘low tech’, is no longer tenable. Building on the recognition based on mounting evidence that old perceptions of the Digital Divide are simplistic and that the Divide encompasses not one but many discontinuities, the nature of such a discontinuity between student and tutor becomes the focus of the argument presented here. Many have argued that increased use and availability of digital technologies in schools bring important benefits and opportunities for learning and teaching strategies but are staff and students able work together to ensure positive outcomes? If not, why might this be the case? In examining the implications of the student/teacher Digital Divide some questions concerning the future direction of education emerge
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