Skip to main content
SpringerLink
Log in
Book cover

International Conference on Theory and Practice of Digital Libraries

TPDL 2017: Research and Advanced Technology for Digital Libraries pp 585–591Cite as

Towards Building Knowledge Resources from Social Media Using Semantic Roles

  • Conference paper
  • First Online:

  • 2356 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10450))

Abstract

Text semantics is a well-hidden treasure, whose deciphering requires deep understanding. Artificial Intelligence enhances computers with human-like judgments, thus decoding the covered message and sharing it between machines is one of the main challenges that the computational linguistics domain faces nowadays. In an attempt to learn how humans communicate, computers use language models derived from human knowledge. While still far from completely understanding insinuated messages in political discourses, computer scientists and linguists have joined efforts in modeling a human-like linguistic behavior. This paper aims to introduce the VoxPopuli platform, an instrument to collect user generated content, to analyze it and to generate a map of semantically-related concepts to capturing crowd intelligence.

This is a preview of subscription content, 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 EPUB and 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

Learn about institutional subscriptions

Notes

  1. 1.

    According to the Directive 95/46/EC of the European Parliament and of the Council, personal data is defined as: “‘personal data’ shall mean any information relating to an identified or identifiable natural person (‘data subject’); an identifiable person is one who can be identified, directly or indirectly, in particular by reference to an identification number or to one or more factors specific to his physical, physiological, economic, cultural or social identity”.

References

  1. Chua, T.-S., Li, J., Moens, M.-F.: Mining User Generated Content. Chapman and Hall/CRC, Boca Raton (2014)

    Google Scholar 

  2. Chen, C.-M., Chen, L.-H.: A novel approach for semantic event extraction from sports webcast text. Multimed. Tools Appl. 71(3), 1937–1952 (2014)

    Article  Google Scholar 

  3. Curteanu, N.: Contrastive meanings of the terms “predicative” and “predicational” in various linguistic theories (i, ii). Comput. Sci. J. Moldova 11(4), 2003 (2003)

    MathSciNet  MATH  Google Scholar 

  4. Daniel, G., Jurafsky, D.: Automatic labeling of semantic roles. Comput. Linguist. 28(3), 245–288 (2002)

    Article  Google Scholar 

  5. Go, A., Bhayani, R., Huang, L.: Twitter Sentiment Classification using Distant Supervision, Technical report (2009)

    Google Scholar 

  6. Gouws, S., Metzler, D., Cai, C., Hovy, E.: Contextual bearing on linguistic variation in social media. In: Proceedings of Workshop on Languages in Social Media, LSM-2011, pp. 20–29 (2011)

    Google Scholar 

  7. Han, B., Baldwin, T.: Lexical normalisation of short text messages: makn sens a #twitter. In: Proceedings of the 49th ACL-HLT 2011, pp. 368–378 (2011)

    Google Scholar 

  8. Hoser, B., Nitschke, T.: Questions on ethics for research in the virtually connected world. Soc. Netw. 32(3), 180–186 (2010). doi:10.1016/j.socnet.2009.11.003

    Article  Google Scholar 

  9. Macovei, A., Gagea, O., Trandabăţ, D.: Towards creating an ontology of social media texts. In: Trandabăţ, D., Gîfu, D. (eds.) RUMOUR 2015. CCIS, vol. 588, pp. 18–31. Springer, Cham (2016). doi:10.1007/978-3-319-32942-0_2

    Google Scholar 

  10. Nakov, P., Ritter, A., Rosenthal, S., Stoyanov, V., Sebastiani, F.: SemEval-2016 task 4: sentiment analysis in Twitter. In: Proceedings of SemEval 2016 (2016)

    Google Scholar 

  11. Russell, M.A.: Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More (2013)

    Google Scholar 

  12. Schlaefer, N., Chu-Carroll, J., Nyberg, E., Fan, J., Zadrozny, W., Ferrucci, D.: Statistical source expansion for question answering. In: Proceedings of CIKM (2011)

    Google Scholar 

  13. James, S.: The wisdom of crowds. Doubleday (ed.) (2005). ISBN: 0-385-50386-5

    Google Scholar 

  14. Diana, T.: Mining Romanian texts for semantic knowledge. In: Proceedings of ISDA 2011, Cordoba, Spain, pp. 1062–1066 (2011)

    Google Scholar 

  15. Trandabăţ, D., Irimia, E., Barbu, M.V., Cristea, D., Tufis, D.: The Romanian language in the digital age. In: White Paper Series, p. 87. Springer (2012). ISBN: 978-3-642-30702-7

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University “Al. I. Cuza” of Iasi, Iași, Romania

    Diana Trandabăț

Authors
  1. Diana Trandabăț
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Diana Trandabăț .

Editor information

Editors and Affiliations

  1. Faculteit der Geesteswetenschappen, Universiteit van Amsterdam , Amsterdam, The Netherlands

    Jaap Kamps

  2. Library & Information Center, University of Patras , Patras, Greece

    Giannis Tsakonas

  3. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

  4. Civil Engineering, University of Thrace , Kimmeria, Greece

    Lazaros Iliadis

  5. Informatics, Ionian University , Kerkyra, Greece

    Ioannis Karydis

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Trandabăț, D. (2017). Towards Building Knowledge Resources from Social Media Using Semantic Roles. In: Kamps, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L., Karydis, I. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2017. Lecture Notes in Computer Science(), vol 10450. Springer, Cham. https://doi.org/10.1007/978-3-319-67008-9_50

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67008-9_50

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67007-2

  • Online ISBN: 978-3-319-67008-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation