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        <title>Sentiment Analysis for Issues Monitoring Using Linguistic Resources</title>
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    <name type="personal">
        <namePart type="given">Ecaterina</namePart>
        <namePart type="family">Rascu</namePart>
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        <namePart type="given">Kai</namePart>
        <namePart type="family">Schirmer</namePart>
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    <name type="personal">
        <namePart type="given">Johann</namePart>
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            <title>Actes de la 12ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs</title>
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        <name type="personal">
            <namePart type="given">Michèle</namePart>
            <namePart type="family">Jardino</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <publisher>ATALA</publisher>
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    <abstract>Sentiment analysis dealing with the identification and evaluation of opinions towards a topic, a company, or a product is an essential task within media analysis. It is used to study trends, determine the level of customer satisfaction, or warn immediately when unfavourable trends risk damaging the image of a company. In this paper we present an issues monitoring system which, besides text categorization, also performs an extensive sentiment analysis of online news and newsgroup postings. Input texts undergo a morpho-syntactic analysis, are indexed using a thesaurus and are categorized into user-specific classes. During sentiment analysis, sentiment expressions are identified and subsequently associated with the established topics. After presenting the various components of the system and the linguistic resources used, we describe in detail SentA, its sentiment analysis component, and evaluate its performance.</abstract>
    <identifier type="citekey">rascu-etal-2005-sentiment</identifier>
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        <url>https://aclanthology.org/2005.jeptalnrecital-long.32</url>
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        <date>2005-06</date>
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            <start>311</start>
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%0 Conference Proceedings
%T Sentiment Analysis for Issues Monitoring Using Linguistic Resources
%A Rascu, Ecaterina
%A Schirmer, Kai
%A Haller, Johann
%Y Jardino, Michèle
%S Actes de la 12ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs
%D 2005
%8 June
%I ATALA
%C Dourdan, France
%F rascu-etal-2005-sentiment
%X Sentiment analysis dealing with the identification and evaluation of opinions towards a topic, a company, or a product is an essential task within media analysis. It is used to study trends, determine the level of customer satisfaction, or warn immediately when unfavourable trends risk damaging the image of a company. In this paper we present an issues monitoring system which, besides text categorization, also performs an extensive sentiment analysis of online news and newsgroup postings. Input texts undergo a morpho-syntactic analysis, are indexed using a thesaurus and are categorized into user-specific classes. During sentiment analysis, sentiment expressions are identified and subsequently associated with the established topics. After presenting the various components of the system and the linguistic resources used, we describe in detail SentA, its sentiment analysis component, and evaluate its performance.
%U https://aclanthology.org/2005.jeptalnrecital-long.32
%P 311-320

Markdown (Informal)

[Sentiment Analysis for Issues Monitoring Using Linguistic Resources](https://aclanthology.org/2005.jeptalnrecital-long.32) (Rascu et al., JEP/TALN/RECITAL 2005)

• Sentiment Analysis for Issues Monitoring Using Linguistic Resources (Rascu et al., JEP/TALN/RECITAL 2005)

ACL

• Ecaterina Rascu, Kai Schirmer, and Johann Haller. 2005. Sentiment Analysis for Issues Monitoring Using Linguistic Resources. In Actes de la 12ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs, pages 311–320, Dourdan, France. ATALA.