Automatic thematic content analysis: Finding frames in news

Daan Odijk, Björn Burscher, Rens Vliegenthart, Maarten De Rijke

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

11 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationSocial Informatics - 5th International Conference, SocInfo 2013, Proceedings
Number of pages13
ISBN (Print)9783319032597
Publication statusPublished - 2013
Externally publishedYes
Event5th International Conference on Social Informatics, SocInfo 2013 - Kyoto, Japan
Duration: 25 Nov 201327 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8238 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference5th International Conference on Social Informatics, SocInfo 2013


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