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EMBEDDIA tools output example corpus of Estonian, Croatian and Latvian news articles 1.0
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Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification
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In: Sensors; Volume 22; Issue 5; Pages: 1899 (2022)
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MULTI-STRATEGY SENTIMENT ANALYSIS OF CONSUMER REVIEWS WITH PARTIAL PHRASE MATCHING ...
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MULTI-STRATEGY SENTIMENT ANALYSIS OF CONSUMER REVIEWS WITH PARTIAL PHRASE MATCHING ...
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Lexicon‐pointed hybrid N‐gram Features Extraction Model (LeNFEM) for sentence level sentiment analysis
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A Tweet Sentiment Classification Approach Using a Hybrid Stacked Ensemble Technique
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In: Information ; Volume 12 ; Issue 9 (2021)
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LDA-Based Topic Modeling Sentiment Analysis Using Topic/Document/Sentence (TDS) Model
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In: Applied Sciences ; Volume 11 ; Issue 23 (2021)
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Abstract:
Customer reviews on the Internet reflect users&rsquo ; sentiments about the product, service, and social events. As sentiments can be divided into positive, negative, and neutral forms, sentiment analysis processes identify the polarity of information in the source materials toward an entity. Most studies have focused on document-level sentiment classification. In this study, we apply an unsupervised machine learning approach to discover sentiment polarity not only at the document level but also at the word level. The proposed topic document sentence (TDS) model is based on joint sentiment topic (JST) and latent Dirichlet allocation (LDA) topic modeling techniques. The IMDB dataset, comprising user reviews, was used for data analysis. First, we applied the LDA model to discover topics from the reviews ; then, the TDS model was implemented to identify the polarity of the sentiment from topic to document, and from document to word levels. The LDAvis tool was used for data visualization. The experimental results show that the analysis not only obtained good topic partitioning results, but also achieved high sentiment analysis accuracy in document- and word-level sentiment classifications.
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Keyword:
polarity detection; sentiment analysis; sentiment classification; topic modeling
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URL: https://doi.org/10.3390/app112311091
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Meta-Learner for Amharic Sentiment Classification
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In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models
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In: Electronics ; Volume 10 ; Issue 21 (2021)
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A Novel Deep Learning ArCAR System for Arabic Text Recognition with Character-Level Representation
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In: Computer Sciences & Mathematics Forum; Volume 2; Issue 1; Pages: 14 (2021)
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A Multilingual Lexicon-based Approach for Sentiment Analysis in Social and Cultural Information System Data
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Context Aware Contrastive Opinion Summarization
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In: IFIP Advances in Information and Communication Technology ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS) ; https://hal.inria.fr/hal-03434805 ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS), Feb 2020, Chennai, India. pp.16-29, ⟨10.1007/978-3-030-63467-4_2⟩ (2020)
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Модели и методы анализа тональности в текстах на башкирском языке ... : Models and methods for sentiment analysis of texts in Bashkir language ...
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ArAutoSenti: Automatic annotation and new tendencies for sentiment classification of Arabic messages
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Mining social media as a measure of equity market sentiment
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Influence des lexiques d'émotions et de sentiments sur l'analyse des sentiments Application à des critiques de livres
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In: CORIA-EARIA 2019 ; https://hal.archives-ouvertes.fr/hal-02448203 ; CORIA-EARIA 2019, Mar 2019, Villeurbanne, France (2019)
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FEEL: a French Expanded Emotion Lexicon
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In: https://hal-lirmm.ccsd.cnrs.fr/lirmm-02136090 ; 2019, ⟨swh:1:dir:35a446bb6f0808aa0db6f5bcd032f43e9ec71591;origin=https://hal.archives-ouvertes.fr/lirmm-02136090;visit=swh:1:snp:9d258bfd8a07f79cb8063b6ac33d6e710bd3e3f3;anchor=swh:1:rev:2266d773cf993b8718a1d7ca1d1bce145118f527;path=/⟩ (2019)
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Overwhelmed by Negative Emotions? Maybe You Are Being Cyber-bullied!
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In: Symposium On Applied Computing ; SAC 2019 - The 34th ACM/SIGAPP Symposium On Applied Computing ; https://hal.archives-ouvertes.fr/hal-02020829 ; SAC 2019 - The 34th ACM/SIGAPP Symposium On Applied Computing, Apr 2019, Limassol, Cyprus. ⟨10.1145/3297280.3297573⟩ (2019)
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