Enriching Live Event Participation with Social Network Content Analysis and Visualization

  • Marco Brambilla
  • Daniele Dell’Aglio
  • Emanuele Della Valle
  • Andrea Mauri
  • Riccardo Volonterio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8798)

Abstract

During live events like conferences or exhibitions, people nowadays share their opinions, multimedia contents, suggestions, related materials, and reports through social networking platforms, such as Twitter. However, live events also feature inherent complexity, in the sense that they comprise multiple parallel sessions or happenings (e.g., in a conference you have several sessions in different rooms). The focus of this research is to improve the experience of (local or remote) attendees, by exploiting the contents shared on the social networks. The framework gathers in real time the tweets related to the event, analyses them and links them to the specific sub-events they refer to. Attendees have an holistic view on what is happening and where, so as to get help when deciding what sub-event to attend. To achieve its goal, the application consumes data from different data sources: Twitter, the official event schedule, plus domain specific content (for instance, in case of a computer science conference, DBLP and Google Scholar). Such data is analyzed through a combination of semantic web, crowdsourcing (e.g., by soliciting further inputs from attendees), and machine learning techniques (including NLP and NER) for building a rich content base for the event. The paradigm is shown at work on a Computer Science conference (WWW 2013)

References

  1. 1.
    Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: C-sparql: a continuous query language for rdf data streams. Int. J. Semant. Comput. 4(1), 3–25 (2010)CrossRefMATHGoogle Scholar
  2. 2.
    Bischof, S., Decker, S., Krennwallner, T., Lopes, N., Polleres, A.: Mapping between rdf and xml with xsparql. J. Data Semant. 1(3), 147–185 (2012)CrossRefGoogle Scholar
  3. 3.
    Bozzon, A., Brambilla, M., Ceri, S.: Answering search queries with crowdsearcher. In: 21st World Wide Web Conference (WWW 2012), pp. 1009–1018 (2012)Google Scholar
  4. 4.
    Bozzon, A., Brambilla, M., Ceri, S., Mauri, A.: Reactive crowdsourcing. In: 22nd World Wide Web Conference, WWW ’13, pp. 153–164 (2013)Google Scholar
  5. 5.
    Celino, I., Dell’Aglio, D., Della Valle, E., Huang, Y., Lee, T., Kim, S.-H., Tresp, V.: Towards BOTTARI: using stream reasoning to make sense of location-based micro-posts. In: García-Castro, R., Fensel, D., Antoniou, G. (eds.) ESWC 2011. LNCS, vol. 7117, pp. 80–87. Springer, Heidelberg (2012)Google Scholar
  6. 6.
    Cornolti, M., Ferragina, P., Ciaramita, M.: A framework for benchmarking entity-annotation systems. In: Proceedings of the 22nd International Conference on World Wide Web, WWW ’13, pp. 249–260 (2013)Google Scholar
  7. 7.
    Gangemi, A.: A comparison of knowledge extraction tools for the semantic web. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 351–366. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Hoffart, J., Suchanek, F.M., Berberich, K., Weikum, G.: Yago2: a spatially and temporally enhanced knowledge base from wikipedia. Artif. Intell. 194, 28–61 (2013)MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Hoffart, J., Yosef, M.A., Bordino, I., Fürstenau, H., Pinkal, M., Spaniol, M., Taneva, B., Thater, S., Weikum, G.: Robust disambiguation of named entities in text. In: Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP2011), pp. 782–792 (2011)Google Scholar
  10. 10.
    Lafferty, J.D., McCallum, A., Pereira, F.C.N.: Conditional random fields: probabilistic models for segmenting and labeling sequence data. In: ICML ’01: Proceedings of the 18th International Conference on Machine Learning, pp. 282–289 (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Marco Brambilla
    • 1
  • Daniele Dell’Aglio
    • 1
  • Emanuele Della Valle
    • 1
  • Andrea Mauri
    • 1
  • Riccardo Volonterio
    • 1
  1. 1.Dipartimento di Elettronica, Informazione e BioingegneriaPolitecnico of MilanoMilanoItaly

Personalised recommendations