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Says who?: automatic text-based content analysis of television news

Published: 28 October 2013 Publication History

Abstract

We perform an automatic analysis of television news programs, based on the closed captions that accompany them. Specifically, we collect all the news broadcasted in over 140 television channels in the US during a period of six months. We start by segmenting, processing, and annotating the closed captions automatically. Next, we focus on the analysis of their linguistic style and on mentions of people using NLP methods. We present a series of key insights about news providers, people in the news, and we discuss the biases that can be uncovered by automatic means. These insights are contrasted by looking at the data from multiple points of view, including qualitative assessment.

References

[1]
C. Castillo, G. De Francisci Morales, and A. Shekhawat. Online matching of web content to closed captions in intonow. In SIGIR demonstration papers, 2013.
[2]
P. R. Center. In Changing News Landscape, Even Television is Vulnerable. Trends in News Consumption., Sep. 2012.
[3]
C. Cieri, D. Graff, M. Liberman, N. Martey, S. Strassel, et al. The TDT-2 text and speech corpus. In Proc. of DARPA Broadcast News Workshop, pages 57--60, 1999.
[4]
I. Flaounas, O. Ali, T. Lansdall, T. De Bie, N. Mosdell, J. Lewis, and N. Cristianini. Research methods in the age of digital journalism. Digital Journalism, 1 (1): 102--116, 2013.
[5]
D. Gibbon, Z. Liu, E. Zavesky, D. Paul, D. F. Swayne, R. Jana, and B. Shahraray. Combining content analysis of television programs with audience measurement. In Proc. of CCNC, pages 754--758. IEEE, 2012.
[6]
P. Giordani, H. Kiers, and M. Del Ferraro. ThreeWay: An R package for three-way component analysis, 2012.
[7]
T. Groseclose and J. Milyo. A measure of media bias. Quarterly Journal of Economics, 120 (4): 1191--1237, 2005.
[8]
R. Gunning. The technique of clear writing. McGraw-Hill New York, 1952.
[9]
M. Henzinger, B.-W. Chang, B. Milch, and S. Brin. Query-Free news search. WWWJ, 8 (2): 101--126, 2005.
[10]
W.-H. Lin. Identifying Ideological Perspectives in Text and Video. PhD thesis, Carnegie Mellon University, Oct. 2008.
[11]
W. H. Lin and A. Hauptmann. News video classification using SVM-based multimodal classifiers and combination strategies. In Proc. of ACM MM, pages 323--326, 2002.
[12]
W. H. Lin, T. Wilson, J. Wiebe, and A. Hauptmann. Which side are you on?: identifying perspectives at the document and sentence levels. In Proc. of CoNLL, CoNLL-X '06, pages 109--116. ACL, 2006.
[13]
H. Misra, F. Hopfgartner, A. Goyal, P. Punitha, and J. Jose. TV news story segmentation based on semantic coherence and content similarity. In Proc. of MMM, volume 5916 of LNCS, pages 347--357, 2010.
[14]
J. S. Morris and P. L. Francia. From network news to cable commentary: The evolution of television coverage of the party conventions. In State of the Parties Conference, 2005.
[15]
S. Oger, M. Rouvier, and G. Linares. Transcription-based video genre classification. In Proc. of ICASSP, pages 5114--5117. IEEE, 2010.
[16]
D. Paranjpe. Learning document aboutness from implicit user feedback and document structure. In Proc. of CIKM, pages 365--374. ACM Press, 2009.
[17]
K. Schoenbach, J. De Ridder, and E. Lauf. Politicians on TV news: Getting attention in dutch and german election campaigns. European Journal of Political Research, 39 (4): 519--531, 2001.
[18]
D. A. Shamma, L. Kennedy, and E. F. Churchill. Tweet the debates: understanding community annotation of uncollected sources. In Proc. of WSM, pages 3--10. ACM, 2009.
[19]
A. F. Smeaton, H. Lee, N. E. O'Connor, S. Marlow, and N. Murphy. TV news story segmentation, personalisation and recommendation. In AAAI Spring Symp. on Intelligent Multimedia Knowledge Management, 2003.
[20]
M. Thelwall, K. Buckley, G. Paltoglou, D. Cai, and A. Kappas. Sentiment strength detection in short informal text. JASIST, 61 (12): 2544--2558, 2010.
[21]
K. Toutanova, D. Klein, C. D. Manning, and Y. Singer. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proc. of NAACL, pages 173--180. ACL, 2003.
[22]
L. Xu, Q. Ma, and M. Yoshikawa. Credibility-oriented ranking of multimedia news based on a material-opinion model. In Proc. of WAIM, pages 290--301, 2011.
[23]
Y. Zhou, L. Nie, O. Rouhani-Kalleh, F. Vasile, and S. Gaffney. Resolving surface forms to Wikipedia topics. In Proc. of COLING, pages 1335--1343. ACL, 2010.

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  • (2019)Multimodal approach for tension levels estimation in news videosMultimedia Tools and Applications10.1007/s11042-019-7691-4Online publication date: 10-May-2019
  • (2016)When face-tracking meets social networks: a story of politics in news videosApplied Network Science10.1007/s41109-016-0003-21:1Online publication date: 1-Jun-2016
  • (2015)An Effective Edge and Texture Based Approach towards Curved Videotext Detection and ExtractionInternational Journal of System Dynamics Applications10.4018/IJSDA.20150701014:3(1-29)Online publication date: 1-Jul-2015
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cover image ACM Conferences
UnstructureNLP '13: Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
October 2013
74 pages
ISBN:9781450324151
DOI:10.1145/2513549
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 28 October 2013

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Author Tags

  1. closed captions
  2. news framing

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CIKM'13
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UnstructureNLP '13 Paper Acceptance Rate 9 of 12 submissions, 75%;
Overall Acceptance Rate 9 of 12 submissions, 75%

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Cited By

View all
  • (2019)Multimodal approach for tension levels estimation in news videosMultimedia Tools and Applications10.1007/s11042-019-7691-4Online publication date: 10-May-2019
  • (2016)When face-tracking meets social networks: a story of politics in news videosApplied Network Science10.1007/s41109-016-0003-21:1Online publication date: 1-Jun-2016
  • (2015)An Effective Edge and Texture Based Approach towards Curved Videotext Detection and ExtractionInternational Journal of System Dynamics Applications10.4018/IJSDA.20150701014:3(1-29)Online publication date: 1-Jul-2015
  • (2015)A Social Network Analysis of Face Tracking in News VideoProceedings of the 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)10.1109/SITIS.2015.30(474-481)Online publication date: 23-Nov-2015
  • (2013)Social media news communitiesProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505623(1679-1684)Online publication date: 27-Oct-2013

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