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      Sentiment Analysis with CNNs and LSTMs

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      ScienceOpen Preprints
      ScienceOpen
      CNNs , LSTMs, Sentiment Analysis
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            Abstract

            In this paper we describe our attempt at producing a state-of-the-art senti- ment classifier using Convolutional Neural Networks (CNNs) and Long Short Term Memory (LSTMs) networks. Our sys- tem leverages a large amount of unlabeled data to pre-train word embeddings. We then use a subset of the unlabeled data to fine tune the embeddings using distant su- pervision. The final CNNs and LSTMs are trained on the SemEval-2017 Twitter dataset where the embeddings are fined tuned again. To boost performances we ensemble several CNNs and LSTMs to- gether. Our approach achieved first rank on all of the five English subtasks amongst 40 teams.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            29 May 2022
            Affiliations
            [1 ] HMR Institute of Technology and Management
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PP3POTQ.v1
            0b05d6b0-15de-4e61-a32c-edb32c1fc37a

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Education,Computer science,Engineering
            LSTMs, CNNs ,Sentiment Analysis

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