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A BERT Framework to Sentiment Analysis of Tweets

journal contribution
posted on 2023-08-30, 20:24 authored by Abayomi Bello, Sin-Chun Ng, Man Fai Leung
Sentiment analysis has been widely used in microblogging sites such as Twitter in recent decades, where millions of users express their opinions and thoughts because of its short and simple manner of expression. Several studies reveal the state of sentiment which does not express sentiment based on the user context because of different lengths and ambiguous emotional information. Hence, this study proposes text classification with the use of bidirectional encoder representations from transformers (BERT) for natural language processing with other variants. The experimental findings demonstrate that the combination of BERT with CNN, BERT with RNN, and BERT with BiLSTM performs well in terms of accuracy rate, precision rate, recall rate, and F1-score compared to when it was used with Word2vec and when it was used with no variant.

History

Refereed

  • Yes

Volume

23

Issue number

1

Publication title

Sensors

ISSN

1424-8220

Publisher

MDPI

File version

  • Submitted version

Language

  • eng

Legacy posted date

2023-01-13

Legacy creation date

2023-01-13

Legacy Faculty/School/Department

Faculty of Science & Engineering

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