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Filtering Relevant Facebook Status Updates for Users of Mobile Devices

Stephan Baumann; Rafael Schirru; Joachim Folz
In: Joaquim Filipe; Ana Fred (Hrsg.). Proceedings of the 5th International Conference on Agents and Artificial Intelligence. International Conference on Agents and Artificial Intelligence (ICAART-2013), February 15-18, Barcelona, Spain, Pages 353-356, ISBN 978-989-8565-38-9, SCITEPRESS, 2013.


In recent years, social networking sites such as Twitter, Facebook, and Google+ have become popular. Many people are already used to accessing their individual news feeds ubiquitously also on mobile devices. However the number of status updates in these feeds is usually high thus making the identification of relevant updates a tedious task. In this paper we present an approach to identify the relevant status updates in a user’s Facebook news feed. The algorithm combines simple features based on the interactions with status updates together with more sophisticated metrics from the field of Social Network Analysis as input for a Support Vector Machine. Optionally the feature space can be extended by a topic model in order to improve the classification accuracy. A first evaluation conducted as live user experiment suggests that the approach can lead to satisfying results for a large number of users.