Daily activities of Web users leave traces on the network as heterogeneous data, whose collection is a detailed account of our life: the books we read in the past can provide an effective information in recommending new books.
People identity corresponding to the on-line user presence constitutes nowadays a detailed picture much broader than in the past. This imposed to any interested subjects (such as public organization but mainly enterprises) to actively participate to these dynamics. Social Media, in particular, represents a privileged space where brands (including political organizations) and their public active audience interacts through disintermediation and reinter-mediation mechanisms. Marketing and Communication sectors of these brands need to carry on a constant and proactive presence in the network to follow and measure the concerning conversations.
Related Projects and Resources
- (2014): A context based model for Sentiment Analysis in Twitter. In: Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics, pp. 2345–2354, Dublin City University and Association for Computational Linguistics, Dublin, Ireland, 2014.
- (2013): Robust Language Learning via Efficient Budgeted Online Algorithms. In: 3rd IEEE ICDM Workshop on Sentiment Elicitation from Natural Text for Information Retrieval and Extraction (SENTIRE), To Appear, Dallas, USA, 2013.
- (2013): UNITOR: Combining Syntactic and Semantic Kernels for Twitter Sentiment Analysis. In: Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pp. 369–374, Association for Computational Linguistics, Atlanta, Georgia, USA, 2013.
- (2013): Enabling Advanced Business Intelligence in Divino.. In: DART@AI*IA, pp. 61-72, 2013.