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SEDAT: Sentiment and Emotion Detection in Arabic Text Using CNN-LSTM Deep Learning.

, , and . ICMLA, page 835-840. IEEE, (2018)

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TeamUNCC at SemEval-2018 Task 1: Emotion Detection in English and Arabic Tweets using Deep Learning., and . SemEval@NAACL-HLT, page 350-357. Association for Computational Linguistics, (2018)SEDAT: Sentiment and Emotion Detection in Arabic Text Using CNN-LSTM Deep Learning., , and . ICMLA, page 835-840. IEEE, (2018)EmoDet at SemEval-2019 Task 3: Emotion Detection in Text using Deep Learning., , and . SemEval@NAACL-HLT, page 200-204. Association for Computational Linguistics, (2019)The chained-cubic tree interconnection network., , and . Int. Arab J. Inf. Technol., 8 (3): 334-343 (2011)Detecting Drinking-Related Contents on Social Media by Classifying Heterogeneous Data Types., , , , , and . IEA/AIE (2), volume 10351 of Lecture Notes in Computer Science, page 364-373. Springer, (2017)Automatic Identification of Fake News Using Deep Learning., , and . SNAMS, page 383-388. IEEE, (2019)MTRecS-DLT: Multi-Modal Transport Recommender System using Deep Learning and Tree Models., , , , , , and . SNAMS, page 274-278. IEEE, (2019)Sentiment Analysis on Arabic Tweets: Challenges to Dissecting the Language., and . HCI (13), volume 10283 of Lecture Notes in Computer Science, page 191-202. Springer, (2017)Sentiment Analysis of Twitter Data: Emotions Revealed Regarding Donald Trump during the 2015-16 Primary Debates., and . ICTAI, page 760-764. IEEE Computer Society, (2017)A feasibility study on identifying drinking-related contents in Facebook through mining heterogeneous data., , , , , and . Health Informatics Journal, (2019)