Social Listening of City Scale Events Using the Streaming Linked Data Framework

  • Marco Balduini
  • Emanuele Della Valle
  • Daniele Dell’Aglio
  • Mikalai Tsytsarau
  • Themis Palpanas
  • Cristian Confalonieri
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8219)


City-scale events may easily attract half a million of visitors in hundreds of venues over just a few days. Which are the most attended venues? What do visitors think about them? How do they feel before, during and after the event? These are few of the questions a city-scale event manger would like to see answered in real-time. In this paper, we report on our experience in social listening of two city-scale events (London Olympic Games 2012, and Milano Design Week 2013) using the Streaming Linked Data Framework.


Data Stream Olympic Game Twitter User Continuous Query Semantic Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Balduini, M., et al.: BOTTARI: An augmented reality mobile application to deliver personalized and location-based recommendations by continuous analysis of social media streams. J. Web Sem. 16, 33–41 (2012)CrossRefGoogle Scholar
  2. 2.
    Balduini, M., Della Valle, E.: Tracking Movements and Attention of Crowds in Real Time Analysing Social Streams – The case of the Open Ceremony of London 2012. In: Semantic Web Challenge at ISWC 2012 (2012)Google Scholar
  3. 3.
    Garofalakis, M., Gehrke, J., Rastogi, R.: Data Stream Management: Processing High-Speed Data Streams. Springer-Verlag New York, Inc. (2007)Google Scholar
  4. 4.
    Della Valle, E., Ceri, S., van Harmelen, F., Fensel, D.: It’s a Streaming World! Reasoning upon Rapidly Changing Information. IEEE Intelligent Systems 24(6), 83–89 (2009)CrossRefGoogle Scholar
  5. 5.
    Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF,
  6. 6.
    Barbieri, D.F., Braga, D., Ceri, S., Della Valle, E., Grossniklaus, M.: Incremental Reasoning on Streams and Rich Background Knowledge. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) ESWC 2010, Part I. LNCS, vol. 6088, pp. 1–15. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Le-Phuoc, D., Dao-Tran, M., Xavier Parreira, J., Hauswirth, M.: A native and adaptive approach for unified processing of linked streams and linked data. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 370–388. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  8. 8.
    Calbimonte, J.-P., Corcho, O., Gray, A.J.G.: Enabling ontology-based access to streaming data sources. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 96–111. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Barbieri, D.F., et al.: C-SPARQL: a Continuous Query Language for RDF Data Streams. Int. J. Semantic Computing 4(1), 3–25 (2010)CrossRefzbMATHGoogle Scholar
  10. 10.
    Anicic, D., Fodor, P., Rudolph, S., Stojanovic, N.: EP-SPARQL: a unified language for event processing and stream reasoning. In: WWW, pp. 635–644 (2011)Google Scholar
  11. 11.
    Bizer, C., Heath, T., Berners-Lee, T.: Linked data - the story so far. Int. J. Semantic Web Inf. Syst. 5(3), 1–22 (2009)CrossRefGoogle Scholar
  12. 12.
    Barbieri, D.F., Della Valle, E.: A proposal for publishing data streams as linked data - a position paper. In: LDOW (2010)Google Scholar
  13. 13.
    Tsytsarau, M., Palpanas, T., Denecke, K.: Scalable Detection of Sentiment-Based Contradictions. In: DiversiWeb Workshop, WWW, Hyberabad, India (2011)Google Scholar
  14. 14.
    Vlachos, M., et al.: Identifying similarities, periodicities and bursts for online search queries. In: SIGMOD Conference, pp. 131–142 (2004)Google Scholar
  15. 15.
    Calabrese, F., Colonna, M., Lovisolo, P., Parata, D., Ratti, C.: Real-time urban monitoring using cell phones: A case study in rome. IEEE Transactions on Intelligent Transportation Systems 12(1), 141–151 (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Marco Balduini
    • 1
  • Emanuele Della Valle
    • 1
  • Daniele Dell’Aglio
    • 1
  • Mikalai Tsytsarau
    • 2
  • Themis Palpanas
    • 2
  • Cristian Confalonieri
    • 3
  1. 1.DEIBPolitecnico di MilanoItaly
  2. 2.DISIUniversitá degli Studi di TrentoItaly
  3. 3.StudiolaboItaly

Personalised recommendations