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Rule-Based Sentiment Analysis in Narrow Domain: Detecting Sentiment in Daily Horoscopes Using Sentiscope / Agić, Željko ; Merkler, Danijela.

By: Agić, Željko.
Contributor(s): Merkler, Danijela [aut].
Material type: materialTypeLabelArticleDescription: 115-124.Other title: Rule-Based Sentiment Analysis in Narrow Domain: Detecting Sentiment in Daily Horoscopes Using Sentiscope [Naslov na engleskom:].Subject(s): 5.04 | sentiment analysis, narrow domain, rule-based system hrv | sentiment analysis, narrow domain, rule-based system engOnline resources: Click here to access online | Click here to access online In: 2nd Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2012) (15.12.2012. ; Mumbai, Indija) Proceedings of the 2nd Workshop on Sentiment Analysis where AI meets Psychology str. 115-124Bandyopadhyay, Sivaji ; Okumura, ManabuSummary: We present a prototype system --- named Sentiscope --- for collecting daily horoscopes from online news portals written in Croatian, detecting polarity phrases and overall sentiment conveyed by these texts and providing sentiment-analysis-based visualizations in a graphical user interface on the web. The system was evaluated using a dataset of daily horoscopes which was manually annotated for (positive and negative) polarity phrases and (positive, negative and neutral) overall sentiment. Linearly weighted kappa coefficient of 0.593 has indicated moderate inter-annotator agreement on overall sentiment annotation. The system achieved an F1-score of 0.566 on overall sentiment and 0.402 on phrase detection. An overview of implementation is provided --- with special emphasis on the polarity phrase detection module implemented in NooJ linguistic IDE --- and the system is made available to users on the web.
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We present a prototype system --- named Sentiscope --- for collecting daily horoscopes from online news portals written in Croatian, detecting polarity phrases and overall sentiment conveyed by these texts and providing sentiment-analysis-based visualizations in a graphical user interface on the web. The system was evaluated using a dataset of daily horoscopes which was manually annotated for (positive and negative) polarity phrases and (positive, negative and neutral) overall sentiment. Linearly weighted kappa coefficient of 0.593 has indicated moderate inter-annotator agreement on overall sentiment annotation. The system achieved an F1-score of 0.566 on overall sentiment and 0.402 on phrase detection. An overview of implementation is provided --- with special emphasis on the polarity phrase detection module implemented in NooJ linguistic IDE --- and the system is made available to users on the web.

Projekt MZOS 037-0372794-2804

Projekt MZOS 130-1300646-1776

ENG

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