115,195 research outputs found

    International student mobility : the role of social networks

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    Building upon recent work on higher education mobility, this paper contends that social networks of friendship and kinship are critical determinants for students deciding to study overseas, not just, as has hitherto been suggested, a complementary factor. It uses original data collected through interviews and focus groups with thirty-eight higher education international students studying at three UK universities and argues that students who choose to study overseas do not operate within a vacuum but rather draw upon extended networks of individuals who have chosen to do so themselves or advocate studying abroad. While this encouragement may be of an explicit and unequivocal nature – telling students that they ought to study overseas – for the majority it is rather more implicit. The students interviewed invariably related that higher education overseas or mobility more generally was an accepted practice amongst their peers, thereby leading to a normalisation of the mobility process. The paper concludes that international students come to accept mobility as a taken for granted stage within the lifecourse, and, whether intentionally or not, this is often the driving force behind their decision to study overseas

    Inference of the Russian drug community from one of the largest social networks in the Russian Federation

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    The criminal nature of narcotics complicates the direct assessment of a drug community, while having a good understanding of the type of people drawn or currently using drugs is vital for finding effective intervening strategies. Especially for the Russian Federation this is of immediate concern given the dramatic increase it has seen in drug abuse since the fall of the Soviet Union in the early nineties. Using unique data from the Russian social network 'LiveJournal' with over 39 million registered users worldwide, we were able for the first time to identify the on-line drug community by context sensitive text mining of the users' blogs using a dictionary of known drug-related official and 'slang' terminology. By comparing the interests of the users that most actively spread information on narcotics over the network with the interests of the individuals outside the on-line drug community, we found that the 'average' drug user in the Russian Federation is generally mostly interested in topics such as Russian rock, non-traditional medicine, UFOs, Buddhism, yoga and the occult. We identify three distinct scale-free sub-networks of users which can be uniquely classified as being either 'infectious', 'susceptible' or 'immune'.Comment: 12 pages, 11 figure

    Emerging technologies for learning (volume 2)

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    Mining social network data for personalisation and privacy concerns: A case study of Facebook’s Beacon

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    This is the post-print version of the final published paper that is available from the link below.The popular success of online social networking sites (SNS) such as Facebook is a hugely tempting resource of data mining for businesses engaged in personalised marketing. The use of personal information, willingly shared between online friends' networks intuitively appears to be a natural extension of current advertising strategies such as word-of-mouth and viral marketing. However, the use of SNS data for personalised marketing has provoked outrage amongst SNS users and radically highlighted the issue of privacy concern. This paper inverts the traditional approach to personalisation by conceptualising the limits of data mining in social networks using privacy concern as the guide. A qualitative investigation of 95 blogs containing 568 comments was collected during the failed launch of Beacon, a third party marketing initiative by Facebook. Thematic analysis resulted in the development of taxonomy of privacy concerns which offers a concrete means for online businesses to better understand SNS business landscape - especially with regard to the limits of the use and acceptance of personalised marketing in social networks
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