@inproceedings{2fce473bc014446b87569abebdb93164,
title = "Automatically extracting frames from media content using syntacting analysis",
abstract = "Content analysis of media framing is difficult to do using keyword or dictionary approaches. This paper presents an automatic Semantic Network Analysis method for extracting framing. This method consists of four steps. (1) Sentences are analysed syntactically; (2) Semantic relations are extracted from the syntactic structure; (3) actors and issues are identified in these semantic relations yielding a semantic network of relations between actors and issues; and (4) the frames are extracted from this semantic network. The method is tested by analysing the framing of the 2008-2009 Gaza war by the international news media, comparing the automatically extracted frames with a manually coded gold standard. Three of four frames had strong reliability (α > .7) and one frame had moderate reliability (α = 0.58). This paves the way for more large scale quantitative content analysis studies of framing effects and dynamics.",
author = "{Van Atteveldt}, Wouter and Tamir Sheafer and Shaul Shenhav",
year = "2013",
doi = "10.1145/2464464.2464504",
language = "American English",
isbn = "9781450318891",
series = "Proceedings of the 5th Annual ACM Web Science Conference, WebSci'13",
publisher = "Association for Computing Machinery",
pages = "423--430",
booktitle = "Proceedings of the 5th Annual ACM Web Science Conference, WebSci'13",
note = "3rd Annual ACM Web Science Conference, WebSci 2013 ; Conference date: 02-05-2013 Through 04-05-2013",
}