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Reliable Online Social Network Data Collection

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Computational Social Networks

Abstract

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 to understand 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 inaccurate 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 that 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.

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Notes

  1. 1.

    http://www.facebook.com/press/info.php?statistics

  2. 2.

    That said, one of the most popular OSNs, Twitter, has recently made some effort to provide researchers with access to part of their data by donating an archive of public data to the US Library of Congress for preservation and research (http://blog.twitter.com/2010/04/tweet-preservation.html).

  3. 3.

    Regional networks have been since removed from Facebook in 2009.

  4. 4.

    http://www.openstreetmap.org/

  5. 5.

    http://www.google.com/latitude/

  6. 6.

    We did not mention the Federal government and Watergate as it was not appropriate to the participants in UK.

  7. 7.

    To realistically simulate publishing for the simulation group, the information was published using Facebook’s “only visible to me” privacy option. Therefore, each user was able to see exactly the information which would have been shared.

  8. 8.

    We conducted the experiment in four runs because of resource constraints: we had 20 mobile phones available, but 80 participants over the experiment.

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Authors and Affiliations

  1. School of Computer Science, University of St Andrews, St Andrews, UK

    Fehmi Ben Abdesslem, Iain Parris & Tristan Henderson

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  1. Fehmi Ben Abdesslem
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Correspondence to Fehmi Ben Abdesslem .

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  1. Auburn, 98071, USA

    Ajith Abraham

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Abdesslem, F.B., Parris, I., Henderson, T. (2012). Reliable Online Social Network Data Collection. In: Abraham, A. (eds) Computational Social Networks. Springer, London. https://doi.org/10.1007/978-1-4471-4054-2_8

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