Modelling social networking behaviour using social networking analysis tools

Garner, Michaela (2013) Modelling social networking behaviour using social networking analysis tools. BSc dissertation, University of Portsmouth.

[img] PDF
Restricted to Registered users only

Download (3666kB)

    Abstract

    Social networking has become such a big part of our everyday lives it is easy to forget that this type of technology is relatively new in technology terms and it is hard to imagine our lives before social networking existed. Social networking has made it easy to communicate with others across vast distances at any time 24 hours a day. As well as the positive effects that social networking sites bring there are also negative effects such as security issues; how safe and protected is the information on such sites.

    This project set out to capture and model the behaviour of users on the social networking site Facebook. For this project to be successful extensive research was required within areas such as social networking analysis and the social networking tool Pajek, and also how users utilise Facebook. This research was imperative as this would prove to give an underlying understanding of the performance of users on Facebook as well as test certain assumptions made during the design and implementation stages. As well as generating the models this project will look into how users share their information on Facebook and if they make use of the privacy settings incorporated that will protect their data.

    In summary primary research was gathered, analysed, designed, and executed in the Pajek system to produce the models that illustrate various attributes of user behaviour in Facebook social networking.

    Item Type: Dissertation
    Departments/Research Groups: Faculty of Technology > School of Computing
    Depositing User: Alice Bentley
    Date Deposited: 12 Sep 2013 09:21
    Last Modified: 28 Jan 2015 12:28
    URI: http://eprints.port.ac.uk/id/eprint/13275

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...