Filtering Relevant Facebook Status Updates for Users of Mobile Devices

Stephan Baumann, Rafael Schirru, Joachim Folz

2013

Abstract

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.

References

  1. Blei, D. M., Ng, A. Y., and Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research, 3:993-1022.
  2. Boccara, N. (2008). Models of opinion formation: influence of opinion leaders. Int. J. Mod. Phys. C, 19(1):93-109.
  3. Cortes, C. and Vapnik, V. (1995). Support-vector networks. Mach. Learn., 20(3):273-297.
  4. Kleinberg, J. M. (1998). Authoritative Sources in a Hyperlinked Environment. In Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 668-677. AAAI Press.
  5. Page, L., Brin, S., Motwani, R., and Winograd, T. (1998). The pagerank citation ranking: Bringing order to the web. Technical report, Stanford University.
  6. Roch, C. H. (2005). The dual roots of opinion leadership. Journal of Politics, 67(1):110-131.
  7. Weng, J., Lim, E.-P., Jiang, J., and He, Q. (2010). Twitterrank: finding topic-sensitive influential twitterers. In Proceedings of the third ACM international conference on Web search and data mining, WSDM 7810, pages 261-270, New York, NY, USA. ACM.
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Paper Citation


in Harvard Style

Baumann S., Schirru R. and Folz J. (2013). Filtering Relevant Facebook Status Updates for Users of Mobile Devices . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 353-356. DOI: 10.5220/0004188003530356


in Bibtex Style

@conference{icaart13,
author={Stephan Baumann and Rafael Schirru and Joachim Folz},
title={Filtering Relevant Facebook Status Updates for Users of Mobile Devices},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2013},
pages={353-356},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004188003530356},
isbn={978-989-8565-38-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Filtering Relevant Facebook Status Updates for Users of Mobile Devices
SN - 978-989-8565-38-9
AU - Baumann S.
AU - Schirru R.
AU - Folz J.
PY - 2013
SP - 353
EP - 356
DO - 10.5220/0004188003530356