Skip to main content
SpringerLink
Log in

Location Oriented Phrase Detection in Microblogs

  • Conference paper
Database Systems for Advanced Applications (DASFAA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8421))

Included in the following conference series:

Abstract

As a successful micro-blogging service, Twitter has demonstrated unprecedented popularity and international reach. Location extraction from micro-blogs (tweets) on this domain is an important challenge and can harness noisy but rich contents. Extracting location information can enable a variety of applications such as query-by-location, local advertising, crises awareness and also systems designed to provide information about events, points of interests (POIs) and landmarks. Considering the high throughput rate in Twitter space, we propose an approach to detect location-oriented phrases solely relying on tweet contents. The system finds associated phrases dedicated to each specific scalable geographical area. We have evaluated our approach based on real-world Twitter dataset from Australia. We conducted a comprehensive comparison between strong local terms (uni-word) and phrases (multi-words). Our experiments verify the system’s capabilities using multiple trending baselines and demonstrate that our phrase based approach can better specify locality instead of words.

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 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. Amitay, E., Har’El, N., Sivan, R., Soffer, A.: Web-a-where: geotagging web content. In: SIGIR, pp. 273–280 (2004)

    Google Scholar 

  2. Backstrom, L., Kleinberg, J.M., Kumar, R., Novak, J.: Spatial variation in search engine queries. In: WWW, pp. 357–366 (2008)

    Google Scholar 

  3. Chang, H.-W., Lee, D., Eltaher, M., Lee, J.: @phillies tweeting from philly? predicting twitter user locations with spatial word usage. In: ASONAM, pp. 111–118 (2012)

    Google Scholar 

  4. Cheng, Z., Caverlee, J., Lee, K.: You are where you tweet: a content-based approach to geo-locating twitter users. In: CIKM, pp. 759–768 (2010)

    Google Scholar 

  5. Cheng, Z., Caverlee, J., Lee, K.: A content-driven framework for geolocating microblog users. ACM TIST 2, 1–2 (2013)

    Google Scholar 

  6. Fink, C., Piatko, C.D., Mayfield, J., Finin, T., Martineau, J.: Geolocating blogs from their textual content. In: AAAI Spring Symposium: Social Semantic Web: Where Web 2.0 Meets Web 3.0, pp. 25–26 (2009)

    Google Scholar 

  7. Hecht, B., Hong, L., Suh, B., Chi, E.H.: Tweets from justin bieber’s heart: the dynamics of the location field in user profiles. In: CHI, pp. 237–246 (2011)

    Google Scholar 

  8. Kelm, P., Schmiedeke, S., Sikora, T.: Multi-modal, multi-resource methods for placing flickr videos on the map. In: ICMR, pp. 52:1–52:8 (2011)

    Google Scholar 

  9. Larson, M., Soleymani, M., Serdyukov, P., Rudinac, S., Wartena, C., Murdock, V., Friedland, G., Ordelman, R., Jones, G.J.F.: Automatic tagging and geotagging in video collections and communities. In: ICMR, pp. 51:1–51:8 (2011)

    Google Scholar 

  10. Li, C., Weng, J., He, Q., Yao, Y., Datta, A., Sun, A., Lee, B.-S.: Twiner: named entity recognition in targeted twitter stream. In: SIGIR, pp. 721–730 (2012)

    Google Scholar 

  11. Liu, X., Zhang, S., Wei, F., Zhou, M.: Recognizing named entities in tweets. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, HLT 2011, vol. 1, pp. 359–367. Association for Computational Linguistics, Stroudsburg (2011)

    Google Scholar 

  12. McCallum, A., Nigam, K.: A comparison of event models for naive bayes text classification. In: AAAI 1998 Workshop on Learning for Text Categorization, pp. 41–48. AAAI Press (1998)

    Google Scholar 

  13. Ritter, A., Clark, S., Mausam, Etzioni, O.: Named entity recognition in tweets: An experimental study. In: EMNLP, pp. 1524–1534. ACL (2011)

    Google Scholar 

  14. Serdyukov, P., Murdock, V., van Zwol, R.: Placing flickr photos on a map. In: SIGIR, pp. 484–491 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information Technology and Electrical Engineering, The University of Queensland, Australia

    Saeid Hosseini, Sayan Unankard, Xiaofang Zhou & Shazia Sadiq

Authors
  1. Saeid Hosseini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sayan Unankard
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaofang Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shazia Sadiq
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore, Singapore

    Sourav S. Bhowmick

  2. Department of Computer Science, Utah State University, Old Main Hill, 4205, 84322-4205, Logan, UT, USA

    Curtis E. Dyreson

  3. Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220, Aalborg Øst, Denmark

    Christian S. Jensen

  4. Department of Computer Science, National University of Singapore, 13 Computing Drive, 117417, Singapore, Singapore

    Mong Li Lee

  5. Department of Computer Science, Udayana University, Jl. Kampus Unud Jimbaran Bali, 80364, Badung, Bali, Indonesia

    Agus Muliantara

  6. Information Systems Engineering, Christian-Albrechts-Universität zu Kiel, Olshausenstrasse 40, 24098, Kiel, Germany

    Bernhard Thalheim

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Hosseini, S., Unankard, S., Zhou, X., Sadiq, S. (2014). Location Oriented Phrase Detection in Microblogs. In: Bhowmick, S.S., Dyreson, C.E., Jensen, C.S., Lee, M.L., Muliantara, A., Thalheim, B. (eds) Database Systems for Advanced Applications. DASFAA 2014. Lecture Notes in Computer Science, vol 8421. Springer, Cham. https://doi.org/10.1007/978-3-319-05810-8_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05810-8_33

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05809-2

  • Online ISBN: 978-3-319-05810-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation