Skip to main content

A Cross-Media Method of Stakeholder Extraction for News Contents Analysis

  • Conference paper
Web-Age Information Management (WAIM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6184))

Included in the following conference series:

Abstract

We are studying contents analysis of multimedia news as a solution to the issue of bias, which multimedia news, as a reflection of the real world, is also facing. For the contents analysis, we use a stakeholder model representing descriptions of different stakeholders, which are defined as the main participants in an event. In this paper, we propose a method of detecting stakeholders as the core component of the stakeholder-oriented analysis. In our work, a stakeholder is assumed to appear in the video clips and be mentioned in the closed captions frequently. Given a series of video clips and their closed captions reporting the same event, we extract stakeholder candidates from both textual and visual descriptions. After that, we calculate the degree of exposure for each candidate to identify stakeholders. We also present experimental results that validate our method.

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 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. Arguello, J., Callan, J.: A bootstrapping approach for identifying stakeholders in public-comment corpora. In: Proc. of the dg.o2007, pp. 20–23 (2007)

    Google Scholar 

  2. Lin, W.H., Haputmann, A.: Identifying news videos’ ideological perspectives using emphatic patterns of visual concepts. In: Proc. of ACM MM 2009, pp. 443–452 (2009)

    Google Scholar 

  3. Liu, J., Birnbaum, L.: Localsavvy: aggregating local points of view about news issues. In: Proc. of the WWW 2008 Workshop on Location and the Web, pp. 33–40 (2008)

    Google Scholar 

  4. Mita, T., Kaneko, T., Hori, O.: Joint Haar-like features for face detection. In: Proc. of ICCV 2005, pp. 1619–1626 (2005)

    Google Scholar 

  5. Morel, J., Yu, G.: Asift: a new framework for fully affine invariant image comparison. SIAM Journal on Imaging Sciences 2(2), 438–469 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  6. Ogasawara, T., Takahashi, T., Ide, I., Murase, H.: People identification in broadcast news video archive by face matching. Technical report of IEICE. PRMU 106(606), 55–60 (2007)

    Google Scholar 

  7. Xu, L., Ma, Q., Yoshikawa, M.: Stakeholder extraction for inconsistency analysis of multimedia news. In: Proc. of WebDB Forumn 2009 (2009)

    Google Scholar 

  8. Zhang, H.J., Kankanhalli, A., Smoliar, S.W.: Automatic partitioning of full-motion video. Multimedia Systems 1(1), 10–28 (1993)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xu, L., Ma, Q., Yoshikawa, M. (2010). A Cross-Media Method of Stakeholder Extraction for News Contents Analysis. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds) Web-Age Information Management. WAIM 2010. Lecture Notes in Computer Science, vol 6184. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14246-8_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14246-8_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14245-1

  • Online ISBN: 978-3-642-14246-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics