Skip to main content

A Descriptive Analysis of Twitter Activity in Spanish around Boston Terror Attacks

  • Conference paper
Computational Collective Intelligence. Technologies and Applications (ICCCI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8083))

Included in the following conference series:

Abstract

On April 16, 2013 two bombs detonated in the Boston Marathon, with the dramatic result of three people killed and more than 180 people injured. The strong social impact that this event produced in the public opinion has been impressed on the social networks that stored opinions, comments, analysis, pictures and other materials. The availability of this large amount of information and computational capability to process it, provides a new way to study social behaviors. In particular, understanding the social network responses to the Boston terror attack can give us some clues to understand its impact on the society. Among the social networks available on Internet, Twitter, given its open nature, provides amazing research opportunities. This paper presents our first step building a Twitter analysis tool in Spanish. We illustrate this approach introducing a description of the activity generated on Twitter around the sentence “Maratón de Boston” (which means “Boston Marathon” in Spanish) along one week after the terror attack. This result will be used to implement a sentiment analysis tool in Spanish. During the observed time frame we have observed little social iteration and a high number of retweets in the Spanish-speaker twitter community.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wasserman, S., Galaskiewicz, J.: Advances in social network analysis: Research in the social and behavioral sciences. SAGE Publications, Incorporated (1994)

    Google Scholar 

  2. Java, A., Song, X., Finin, T., Tseng, B.: Why we twitter: understanding microblogging usage and communities. In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, pp. 56–65. ACM (2007)

    Google Scholar 

  3. Sakaki, T., Okazaki, M., Matsuo, Y.: Earthquake shakes twitter users: real-time event detection by social sensors. In: Proceedings of the 19th International Conference on World Wide Web, pp. 851–860. ACM (2010)

    Google Scholar 

  4. Paul, M., Dredze, M.: You are what you tweet: Analyzing twitter for public health. In: Fifth International AAAI Conference on Weblogs and Social Media, ICWSM 2011 (2011)

    Google Scholar 

  5. Cataldi, M., Di Caro, L., Schifanella, C.: Emerging topic detection on twitter based on temporal and social terms evaluation. In: Proceedings of the Tenth International Workshop on Multimedia Data Mining, p. 4. ACM (2010)

    Google Scholar 

  6. Hayes, B.: Graph Theory in Practice: Part I. American Scientist 88(1), 9–13 (2000)

    Google Scholar 

  7. Hayes, B.: Graph Theory in Practice: Part II. American Scientist 88(2), 104–109 (2000)

    Google Scholar 

  8. Luciano, Rodrigues, F.A., Travieso, G., Boas, V.P.R.: Characterization of complex networks: A survey of measurements. Advances in Physics 56(1), 167–242 (2006)

    Google Scholar 

  9. Castillo, C., Mendoza, M., Poblete, B.: Information credibility on twitter. In: Proceedings of the 20th International Conference on World Wide Web, pp. 675–684. ACM (2011)

    Google Scholar 

  10. Thelwall, M., Buckley, K., Paltoglou, G.: Sentiment strength detection for the social web. Journal of the American Society for Information Science and Technology 63(1), 163–173 (2012)

    Article  Google Scholar 

  11. Pak, A., Paroubek, P.: Twitter as a corpus for sentiment analysis and opinion mining. In: Proceedings of the International Conference on Language Resources and Evaluation (LREC), vol. 2010 (2010)

    Google Scholar 

  12. Bello-Orgaz, G., Menendez, H., Camacho, D.: Adaptive k-means algorithm for overlapped graph clustering. International Journal of Neural Systems 22(05), 1–19 (2012)

    Article  Google Scholar 

  13. Menendez, H., Bello-Orgaz, G., Camacho, D.: Extracting behavioural models from 2010 fifa world cup. Journal of Systems Science and Complexity 26(1), 43–61 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cuesta, Á., Barrero, D.F., R-Moreno, M.D. (2013). A Descriptive Analysis of Twitter Activity in Spanish around Boston Terror Attacks. In: Bǎdicǎ, C., Nguyen, N.T., Brezovan, M. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2013. Lecture Notes in Computer Science(), vol 8083. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40495-5_63

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40495-5_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40494-8

  • Online ISBN: 978-3-642-40495-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics