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International Conference on Social Informatics

SocInfo 2013: Social Informatics pp 333–345Cite as

Automatic Thematic Content Analysis: Finding Frames in News

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8238))

Abstract

Framing in news is the way in which journalists depict an issue in terms of a ‘central organizing idea.’ Frames can be a perspective on an issue. We explore the automatic classification of four generic news frames: conflict, human interest, economic consequences, and morality. Complex characteristics of messages such as frames have been studied using thematic content analysis. Indicator questions are formulated, which are then manually coded by humans after reading a text and combined into a characterization of the message. We operationalize this as a classification task and, inspired by the way-of-working of media analysts, we propose a two-stage approach, where we first rate a news article using indicator questions for a frame and then use the outcomes to predict whether a frame is present. We approach human accuracy on almost all indicator questions and frames.

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Author information

Authors and Affiliations

  1. Intelligent System Labs Amsterdam (ISLA), University of Amsterdam, The Netherlands

    Daan Odijk & Maarten de Rijke

  2. Department of Communication Science, Amsterdam School of Communication Research (ASCoR), University of Amsterdam, The Netherlands

    Björn Burscher & Rens Vliegenthart

Authors
  1. Daan Odijk
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  2. Björn Burscher
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  3. Rens Vliegenthart
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  4. Maarten de Rijke
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Editor information

Editors and Affiliations

  1. Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshida-Honmachi, 606-8501, Sakyo-ku, Kyoto, Japan

    Adam Jatowt

  2. School of Information Systems, Singapore Management University, 80 Stamford Road, 178902, Singapore

    Ee-Peng Lim  & Bing Tian Dai  & 

  3. Department of Information and Library Science, School of Informatics and Computing, Indiana University, 1320 E. 10th St., LI 011, 47405, Bloomington, IN, USA

    Ying Ding

  4. Department of Integrated Psychological Sciences, Kwansei Gakuin University, 1-1-155 Uegahara, 662-8501, Nishinomiya, Hyogo, Japan

    Asako Miura

  5. Faculty of Library, Information and Media Science, University of Tsukuba, 1-2 Kasuga, 305-8550, Tsukuba City, Ibaraki, Japan

    Taro Tezuka

  6. Department of Computer Science, University of Caen Basse-Normandie, Campus Côte de Nacre, F-14032, Caen Cedex, France

    Gaël Dias

  7. Department of Social Informatics, Graduate School of Informatics,, Kyoto University, 606-8501, Kyoto, Japan

    Katsumi Tanaka

  8. Department of Communication, University of California, 93106, Santa Barbara, CA, USA

    Andrew Flanagin

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© 2013 Springer International Publishing Switzerland

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Odijk, D., Burscher, B., Vliegenthart, R., de Rijke, M. (2013). Automatic Thematic Content Analysis: Finding Frames in News. In: Jatowt, A., et al. Social Informatics. SocInfo 2013. Lecture Notes in Computer Science, vol 8238. Springer, Cham. https://doi.org/10.1007/978-3-319-03260-3_29

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  • DOI: https://doi.org/10.1007/978-3-319-03260-3_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03259-7

  • Online ISBN: 978-3-319-03260-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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