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Aspect-Level Sentiment Analysis in Czech

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F14%3A43923465" target="_blank" >RIV/49777513:23520/14:43923465 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Aspect-Level Sentiment Analysis in Czech

  • Original language description

    This paper presents a pioneering research on aspect-level sentiment analysis in Czech. The main contribution of the paper is the newly created Czech aspect-level sentiment corpus, based on data from restaurant reviews. We annotated the corpus with two variants of aspect-level sentiment aspect terms and aspect categories. The corpus consists of 1,244 sentences and 1,824 annotated aspects and is freely available to the research community. Furthermore, we propose a baseline system based on supervised machine learning. Our system detects the aspect terms with F-measure 68.65% and their polarities with accuracy 66.27%. The categories are recognized with F-measure 74.02% and their polarities with accuracy 66.61%.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - New Technologies for Information Society</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    5th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2014, Proceedings of the Workshop

  • ISBN

    978-1-941643-11-2

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    24-30

  • Publisher name

    Association for Computational Linguistics (ACL)

  • Place of publication

    209 N. Eighth Stree, Stroudsburg, PA 18360, USA

  • Event location

    Baltimore, USA

  • Event date

    Jun 27, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article