Skip to main content
SpringerLink
Log in

Spatio-Temporal-Thematic Analysis of Citizen Sensor Data: Challenges and Experiences

  • Conference paper
Web Information Systems Engineering - WISE 2009 (WISE 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5802))

Included in the following conference series:

Abstract

We present work in the spatio-temporal-thematic analysis of citizen-sensor observations pertaining to real-world events. Using Twitter as a platform for obtaining crowd-sourced observations, we explore the interplay between the 3 dimensions in extracting insightful summaries of observations. We present our experiences in building a web mashup application, Twitris[1] that also facilitates the spatio-temporal-thematic exploration of social signals underlying events.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Twitris: Twitter through space, time and theme, http://twitris.dooduh.com

  2. Jain, R.: Experiential computing. Commun. ACM 46(7), 48–55 (2003)

    Article  Google Scholar 

  3. Zhao, Q., Mitra, P., Chen, B.: Temporal and information flow based event detection from social text streams. In: AAAI, pp. 1501–1506 (2007)

    Google Scholar 

  4. Yang, Y., Pierce, T., Carbonell, J.: A study of retrospective and on-line event detection. In: SIGIR 1998, pp. 28–36. ACM, New York (1998)

    Chapter  Google Scholar 

  5. Kumar, R., Mahadevan, U., Sivakumar, D.: A graph-theoretic approach to extract storylines from search results. In: KDD, pp. 216–225 (2004)

    Google Scholar 

  6. Adam, E.: Fighter cockpits of the future, October 1993, pp. 318–323 (1993)

    Google Scholar 

  7. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)

    Article  Google Scholar 

  8. Turney, P.: Extraction of keyphrases from text: Evaluation of four algorithms. Technical report, National Research Council, Institute for Information Technology (1997)

    Google Scholar 

  9. Church, K.W., Hanks, P.: Word association norms, mutual information, and lexicography. In: Proceedings of the 27th annual meeting on ACL (1989)

    Google Scholar 

  10. Thomas, C., Mehra, P., Brooks, R., Sheth, A.P.: Growing fields of interest - using an expand and reduce strategy for domain model extraction. In: Web Intelligence, pp. 496–502 (2008)

    Google Scholar 

  11. Klein, G., Moon, B., Hoffman, R.: Making sense of sensemaking 1: alternative perspectives. IEEE Intelligent Systems 21(4), 70–73 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Knoesis Center, Wright State University, Dayton, OH, USA

    Meenakshi Nagarajan, Karthik Gomadam, Amit P. Sheth, Ajith Ranabahu, Raghava Mutharaju & Ashutosh Jadhav

Authors
  1. Meenakshi Nagarajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karthik Gomadam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Amit P. Sheth
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ajith Ranabahu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Raghava Mutharaju
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ashutosh Jadhav
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. European Research Center for Information Systems, University of Münster,, Leonardo Campus 3, 48149, Münster, Germany

    Gottfried Vossen

  2. Dept. of Computer Science, School of Engineering, University of California, 95064, Santa Cruz, CA, USA

    Darrell D. E. Long

  3. Dept. of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, William M. W. Mong Engineering Building, Shatin, N. T.,, Hong Kong, China

    Jeffrey Xu Yu

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nagarajan, M., Gomadam, K., Sheth, A.P., Ranabahu, A., Mutharaju, R., Jadhav, A. (2009). Spatio-Temporal-Thematic Analysis of Citizen Sensor Data: Challenges and Experiences. In: Vossen, G., Long, D.D.E., Yu, J.X. (eds) Web Information Systems Engineering - WISE 2009. WISE 2009. Lecture Notes in Computer Science, vol 5802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04409-0_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-04409-0_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04408-3

  • Online ISBN: 978-3-642-04409-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation