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Sentiment Analysis for Media Reputation Research

Läubli, Samuel; Schranz, Mario; Christen, Urs; Klenner, Manfred (2012). Sentiment Analysis for Media Reputation Research. In: The 11th Conference on Natural Language Processing (KONVENS 2012), Vienna, 19 September 2012 - 21 September 2012. ÖGAI, 274-281.

Abstract

As a subtask of qualitative media reputation research, human annotators manually encode the polarity of actors in media products. Seeking to automate this process, wehave implemented twobaseline classifiers that categorize actors in newspaper articles under six and four polarityclasses. Experiments have shown that our approach is not suitable for distinguishing between six finegrained classes, which has turned out to bedifficult for humans also. In contrast, we have obtained promising results for the fourclass model, through which we argue thatautomated sentiment analysis has a considerable potential in qualitative reputation research.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Scopus Subject Areas:Physical Sciences > Software
Language:English
Event End Date:21 September 2012
Deposited On:05 Oct 2012 07:10
Last Modified:17 Mar 2022 08:10
Publisher:ÖGAI
OA Status:Green
Official URL:http://www.oegai.at/konvens2012/proceedings.shtml
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