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Dictionary-Based Sentiment Analysis Applied to a Specific Domain
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In: 2nd and 3rd International Symposium on Information Management and Big Data - Revised Selected Papers ; SIMBIg: Symposium on Information Management and Big Data ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-01910683 ; SIMBIg: Symposium on Information Management and Big Data, Sep 2016, Cusco, Peru. pp.57-68, ⟨10.1007/978-3-319-55209-5_5⟩ ; https://simbig.org/SIMBig2016/ (2016)
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Optimizing Short Message Text Sentiment Analysis for Mobile Device Forensics
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In: IFIP Advances in Information and Communication Technology ; 12th IFIP International Conference on Digital Forensics (DF) ; https://hal.inria.fr/hal-01758674 ; 12th IFIP International Conference on Digital Forensics (DF), Jan 2016, New Delhi, India. pp.69-87, ⟨10.1007/978-3-319-46279-0_4⟩ (2016)
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The predictive power of stock micro-blogging sentiment in forecasting stock market behaviour
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French Social Media Mining : Expertise and Sentiment ; Fouille des médias sociaux français : expertise et sentiment
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In: https://hal-lirmm.ccsd.cnrs.fr/tel-01507494 ; Artificial Intelligence [cs.AI]. Université Montpellier, 2016. English. ⟨NNT : 2016MONTT249⟩ (2016)
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A semi-automatic method for constructing MUSE sentiment-annotated corpora ; Une méthode semi-automatique de construction des corpus MUSE annotés en sentiments
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In: ICAL ; https://hal.archives-ouvertes.fr/hal-01526827 ; ICAL, Nguyen Tat Thanh University, Dec 2016, Ho Chi Minh City, Vietnam. pp.17-18 ; http://ical.amu.edu.pl/ (2016)
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A Pragma-Semantic Analysis of the Emotion/Sentiment Relation in Debates
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In: 4th International Workshop on Artificial Intelligence and Cognition ; https://hal.inria.fr/hal-01342438 ; 4th International Workshop on Artificial Intelligence and Cognition, Jul 2016, New York, United States (2016)
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| 7 |
Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques
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Opinion Mining And Sentiment Analysis Techniques: A Recent Survey ...
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Ανάλυση ελληνικής κοινής γνώμης στο Twitter βασισμένη σε λεξικό ...
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| 11 |
Minería de Opiniones basado en la adaptación al español de ANEW sobre opiniones acerca de hoteles ; Opinion Mining based on the Spanish adaptation of ANEW on hotel customer comments
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Abstract:
La minería de opiniones (MO) ha mostrado una alta tendencia de investigación en los últimos años debido a la producción en gran escala de opiniones y comentarios por parte de usuarios activos en Internet. Las empresas y organizaciones en general están interesadas en conocer cuál es la reputación que tienen de sus usuarios en las redes sociales, blogs, wikis y otros sitios web. Hasta ahora, la gran mayoría de trabajos de investigación involucran sistemas de MO en el idioma inglés. Por este motivo, la comunidad científica está interesada en trabajos diferentes a este lenguaje. En este artículo se muestra la construcción de un sistema de minería de opiniones en español sobre comentarios dados por clientes de diferentes hoteles. El sistema trabaja bajo el enfoque léxico utilizando la adaptación al español de las normas afectivas para las palabras en inglés (ANEW). Estas normas se basan en las evaluaciones que se realizaron en las dimensiones de valencia, excitación y el dominio. Para la construcción del sistema se tuvo en cuenta las fases de extracción, preprocesamiento de textos, identificación del sentimiento y la respectiva clasificación de la opinión utilizando ANEW. Los experimentos del sistema se hicieron sobre un corpus etiquetado proveniente de la versión en español de Tripadvisor. Como resultado final se obtuvo una precisión del 94% superando a sistemas similares. ; Recently, the Opinions Mining (OM) has shown a high tendency of research due to large-scale production of opinions and comments from users over the Internet. Companies and organizations, in general terms, are interested in knowing what is the reputation they have in social networks, blogs, wikis and other web sites. So far, the vast majority of research involving systems MO in English. For this reason, the scientific community is interested in researching different to this language. This article is about the construction of a mining system views in Spanish based on comments given by different clients and hotels. The system works on the lexical approach using Spanish adaptation of affective standards for English words (ANEW). These standards are based on evaluations conducted in the dimensions of valence, arousal and dominance. For the construction of the system took into account the phases of extraction, preprocessing of texts, identification of feelings and the respective ranking of the opinion using ANEW. System experiments were made on labeling a corpus from the Spanish version of Tripadvisor. As a result, precision exceeding 94% was obtained at similar systems.
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Keyword:
Análisis de sentimiento; ANEW; Lenguajes y Sistemas Informáticos; Lexicon; Lexicón; Minería de opinión; NLP; Opinion mining; PLN; Sentiment analysis
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URL: http://hdl.handle.net/10045/53558
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| 12 |
Improving sentiment analysis through ensemble learning of meta-level features
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Análise de sentimentos baseada em aspectos e atribuições de polaridade ; Aspect-based sentiment analysis and polarity assignment
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| 14 |
Pattern-based automatic induction of domain adapted resources for social media analysis
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In: TDX (Tesis Doctorals en Xarxa) (2016)
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| 15 |
Multilingual Sentiment Analysis: State of the Art and Independent Comparison of Techniques
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Detecting subjectivity through lexicon-grammar. strategies databases, rules and apps for the italian language
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A Lexicon-based Approach for Sentiment Classification of Amazon Books Reviews in Italian Language
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| 19 |
Mining and Analyzing Subjective Experiences in User Generated Content
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In: Browse all Theses and Dissertations (2016)
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