robust project full details
Champion:
Harith Alani
KMi Director
Participant(s):Yulan He, Matthew Rowe, Sofia Angeletou, Gregoire Burel, Hassan Saif, Miriam Fernandez, Smitashree Choudhury, Keerthi Thomas
Similar Projects:WeGov
Timeline:01 Nov 2010 - 31 Oct 2013
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ROBUST
ROBUST aims to analyze, manage and care for online communities to support their well being & to measure their created value.
Online communities have emerged in all areas of society, and their use is now widespread in social, business, scientific and public service domains. They enable the community members to collaborate through shared ideas, knowledge and opinion. Thus, online communities generate major economic value to business and can form pivotal parts of corporate expertise management, corporate marketing, product support, customer relationship management, product innovation and targeted advertising.
The objective of ROBUST is to analyze, manage and care for online communities, in order support their well being, to provide access to the created values and to exploit the knowledge and information contained within. This requires the development of metrics, models and algorithms in several fields.
ROBUST is a 3 year, �6.8M EU project with a consortium of 10 partners from 6 countries. ROBUST is led by the University of Koblenz-Landau, and involves the companies of IBM, SAP, Polecat, Temis, and SoftwareMind, as well as the academic institutions of OU KMi, University of Southampton, National University of Ireland, and the Technical University of Berlin.
Partners
Burel, G. and He, Y. (2014). Quantising contribution effort in online communities. In: 23rd International Conference on World Wide Web, 7-11 Apr 2014, Seoul, Korea. https://oro.open.ac.uk/44017/.
Boden, C., Karnstedt, M., Fernández, M. and Volker, M. (2013). Large-scale social-media analytics on stratosphere. In: 22nd International World Wide Web Conference (WWW 2013), 13-17 May 2014, Rio de Janeiro, Brazil. https://oro.open.ac.uk/41397/.
Saif, H., Fernández, M., He, Y. and Alani, H. (2013). Evaluation datasets for Twitter sentiment analysis: a survey and a new dataset, the STS-Gold. In: 1st Interantional Workshop on Emotion and Sentiment in Social and Expressive Media: Approaches and Perspectives from AI (ESSEM 2013), 3 Dec 2013, Turin, Italy. https://oro.open.ac.uk/40660/.
He, Y., Saif, H., Wei, Z. and Wong, K.F. (2012). Quantising opinions for political tweets analysis. In: LREC 2012, Eighth International Conference on Language Resources and Evaluation, 21-27 May 2012, Istanbul, Turkey. https://oro.open.ac.uk/40659/.
Choudhury, S. and Alani, H. (2014). Exploring user behavior and needs in Q & A communities. In: European Conference on Social Media (ECSM 2014), 10-11 Jul 2014, Brighton, UK. https://oro.open.ac.uk/40658/.
Fernandez, M., Alani, H. and Brown, S. (2013). OU Social: reaching students in social media. In: 12th International Semantic Web Conference (ISWC 2013), 21-25 Oct 2013, Sydney, Australia. https://oro.open.ac.uk/38977/.
Saif, H., He, Y. and Alani, H. (2011). Semantic smoothing for Twitter sentiment analysis. In: 10th International Semantic Web Conference (ISWC 2011), 23-27 Oct 2011, Bonn, Germany. https://oro.open.ac.uk/38502/.
Rowe, M., Fernandez, M. and Alani, H. (2013). Modelling and analysis of user behaviour in online communities. IEEE Computer Society Special Technical Community on Social Networking E-Letter, 1(2), https://oro.open.ac.uk/38503/.
Saif, H., He, Y. and Alani, H. (2012). Alleviating data sparsity for Twitter sentiment analysis. In: 2nd Workshop on Making Sense of Microposts (#MSM2012): Big things come in small packages at the 21st International Conference on theWorld Wide Web (WWW'12), 16 Apr 2012, Lyon, France. https://oro.open.ac.uk/38501/.
Saif, H., He, Y. and Alani, H. (2012). Semantic sentiment analysis of twitter. In: The 11th International Semantic Web Conference (ISWC 2012), 11-15 Nov 2012, Boston, MA, USA. https://oro.open.ac.uk/34929/.
