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Sentiment analysis from online reviews drawing researchers\u2019 attention from various organizations such as academics, government, and private industries. Sentiment analysis has been a hot research topic in Machine Learning (ML) and Natural Language Processing (NLP). Currently, Deep Learning (DL) techniques are implemented in sentiment analysis to get excellent results. This study proposed a hybrid convolutional neural network-long short-term memory (CNN-LSTM) model for sentiment analysis. Our proposed model is being applied with dropout, max pooling, and batch normalization to get results. Experimental analysis carried out on Airlinequality and Twitter airline sentiment datasets. We employed the Keras word embedding approach, which converts texts into vectors of numeric values, where similar words have small vector distances between them. We calculated various parameters, such as accuracy, precision, recall, and F1-measure, to measure the model\u2019s performance. These parameters for the proposed model are better than the classical ML models in sentiment analysis. Our results analysis demonstrates that the proposed model outperforms with 91.3% accuracy in sentiment analysis.<\/jats:p>","DOI":"10.1145\/3457206","type":"journal-article","created":{"date-parts":[[2021,7,21]],"date-time":"2021-07-21T21:12:38Z","timestamp":1626901958000},"page":"1-15","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":119,"title":["A Hybrid CNN-LSTM: A Deep Learning Approach for Consumer Sentiment Analysis Using Qualitative User-Generated Contents"],"prefix":"10.1145","volume":"20","author":[{"given":"Praphula Kumar","family":"Jain","sequence":"first","affiliation":[{"name":"Indian Institute of Technology (Indian School of Mines), Dhanbad, JH, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vijayalakshmi","family":"Saravanan","sequence":"additional","affiliation":[{"name":"Rochester Institute of Technology, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajendra","family":"Pamula","sequence":"additional","affiliation":[{"name":"Indian Institute of Technology (Indian School of Mines), Dhanbad, JH, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,21]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Mohammad Shehab, and Alhareth Mohammed Abu Hussein.","author":"Abualigah Laith","year":"2020","unstructured":"Laith Abualigah , Hamza Essam Alfar , Mohammad Shehab, and Alhareth Mohammed Abu Hussein. 2020 . 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