Building a Twitter Sentiment Analysis System with Recurrent Neural Networks
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Synergy Crowds OÜ, 10141 Tallin, Estonia
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Department of Computer Science, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
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Business Information Systems Department, Interdisciplinary Centre for Data Science, Babeş-Bolyai University, 400083 Cluj-Napoca, Romania
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Coaching Consult, 400191 Cluj-Napoca, Romania
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Department of Management, Babeş-Bolyai University, 400591 Cluj-Napoca, Romania
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Author to whom correspondence should be addressed.
Academic Editor: Nilanjan Sarkar
Sensors 2021, 21(7), 2266; https://doi.org/10.3390/s21072266
Received: 10 February 2021
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Revised: 14 March 2021
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Accepted: 22 March 2021
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Published: 24 March 2021
(This article belongs to the Special Issue Emotion Recognition in Human-Machine Interaction)
This paper presents a sentiment analysis solution on tweets using Recurrent Neural Networks (RNNs). The method is can classifying tweets with an 80.74% accuracy rate, considering a binary task, after experimenting with 20 different design approaches. The solution integrates an attention mechanism aiming to enhance the network, with a two-way localization system: at memory cell level and at network level. We present an in-depth literature review for Twitter sentiment analysis and the building blocks that grounded the design decisions of our solution, employed as a core classification component within a sentiment indicator of the SynergyCrowds platform.
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Keywords:
sentiment analysis; recurrent neural network; twitter; classification; attention mechanism
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Nistor, S.C.; Moca, M.; Moldovan, D.; Oprean, D.B.; Nistor, R.L. Building a Twitter Sentiment Analysis System with Recurrent Neural Networks. Sensors 2021, 21, 2266. https://doi.org/10.3390/s21072266
AMA Style
Nistor SC, Moca M, Moldovan D, Oprean DB, Nistor RL. Building a Twitter Sentiment Analysis System with Recurrent Neural Networks. Sensors. 2021; 21(7):2266. https://doi.org/10.3390/s21072266
Chicago/Turabian StyleNistor, Sergiu C., Mircea Moca, Darie Moldovan, Delia B. Oprean, and Răzvan L. Nistor. 2021. "Building a Twitter Sentiment Analysis System with Recurrent Neural Networks" Sensors 21, no. 7: 2266. https://doi.org/10.3390/s21072266
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