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There is high ambiguity of emotion in text data. In this paper, we consider the sentence-level sentiment classification task, and propose a novel type of convolutional neural network combined with fuzzy logic called the Fuzzy Convolutional Neural Network (FCNN) and its associated learning algorithm. The new model is an integration of modified Convolutional Neural Network (CNN) in the fuzzy logic domain. The proposed model benefits from the use of fuzzy membership degrees to produce more refined outputs, thereby reducing the ambiguities in emotional aspects of sentiment classification. Also it benefits from extracting high-level emotional features due to convolutional neural representation. We compare the performance of our proposed approach with conventional CNN for sentiment classification. The experimental results indicate that the proposed FCNN outperforms the conventional methods for sentiment classification task.<\/jats:p>","DOI":"10.3233\/jifs-169843","type":"journal-article","created":{"date-parts":[[2018,7,20]],"date-time":"2018-07-20T12:29:53Z","timestamp":1532089793000},"page":"6025-6034","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":38,"title":["A fuzzy convolutional neural network for text sentiment analysis"],"prefix":"10.1177","volume":"35","author":[{"given":"Tuan-Linh","family":"Nguyen","sequence":"first","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Sankyuk-Dong, Daegu, South Korea"}]},{"given":"Swathi","family":"Kavuri","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Sankyuk-Dong, Daegu, South Korea"}]},{"given":"Minho","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Electronics Engineering, Kyungpook National University, Sankyuk-Dong, Daegu, South Korea"}]}],"member":"179","published-online":{"date-parts":[[2018,7,18]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"crossref","unstructured":"BeckerW. 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