Social reader: towards browsing the social web

  • Authors:

  • Brett Adams;Dinh Phung;Svetha Venkatesh

  • Affiliations:

  • Department of Computing, Curtin University, Western Australia, Australia 6102;Centre for Pattern Recognition and Data Analytics, School of Information Technology, Deakin University, Victoria, Australia 3220;Centre for Pattern Recognition and Data Analytics, School of Information Technology, Deakin University, Victoria, Australia 3220

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2014

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Abstract

We describe Social Reader, a feed-reader-plus-social-network aggregator that mines comments from social media in order to display a user's relational neighborhood as a navigable social network. Social Reader's network visualization enhances mutual awareness of blogger communities, facilitates their exploration and growth with a fully dragn- drop interface, and provides novel ways to filter and summarize people, groups, blogs and comments. We discuss the architecture behind the reader, highlight tasks it adds to the workflow of a typical reader, and assess their cost. We also explore the potential of mood-based features in social media applications. Mood is particularly relevant to social media, reflecting the personal nature of the medium. We explore two prototype mood-based features: colour coding the mood of recent posts according to a valence/arousal map, and a mood-based abstract of recent activity using image media. A six week study of the software involving 20 users confirmed the usefulness of the novel visual display, via a quantitative analysis of use logs, and an exit survey.