Long short-term memory-based sentiment classification of cloud dataset

Conference paper

Raza, Muhammad Raheel, Hussain, Walayat and Merigo, Jose. (2021). Long short-term memory-based sentiment classification of cloud dataset. 2021 Innovations in Intelligent Systems and Applications Conference . Elazig, Turkey 06 - 08 Oct 2021 Turkey: IEEE Xplore. pp. 1-6 https://doi.org/10.1109/ASYU52992.2021.9598999
AuthorsRaza, Muhammad Raheel, Hussain, Walayat and Merigo, Jose
TypeConference paper
Abstract

Text Sentiment Classification is a crucial task for various decision-making processes in many organizations. It identifies the polarity of texts positively and negatively and highlights the opinions and views hidden within the comments or reviews of a product or service. Performing it on big data from social media and related sources is quite tricky and time-consuming. Nowadays, Deep Learning (DL) is widely used for sentiment analysis due to its high performance. In this paper, Recurrent Neural Network (RNN) based Long Short-Term Memory (LSTM) approach is applied to perform sentiment analysis of a cloud review dataset. The cloud review dataset contains cloud consumer reviews regarding the services provided by different cloud service providers and the dataset is achieved as a result of the Harvesting-as-a-Service (HaaS) framework. The study focuses on observing the behaviour of the deep learning RNN-LSTM approach on a cloud dataset. Results of the experiment are evaluated using various evaluation and performance metrics. The approach tends to achieve 95 % accuracy.

KeywordsMeasurement; Deep learning; Sentiment analysis; Technological innovation; Recurrent neural networks; Social networking (online); Computational modeling
Year01 Jan 2021
PublisherIEEE Xplore
Digital Object Identifier (DOI)https://doi.org/10.1109/ASYU52992.2021.9598999
Web address (URL)https://ieeexplore.ieee.org/xpl/conhome/9598463/proceeding
Open accessPublished as non-open access
Research or scholarlyResearch
Page range1-6
ISBN9781665434058
Web address (URL) of conference proceedingshttps://ieeexplore.ieee.org/xpl/conhome/9598463/proceeding
Output statusPublished
Publication dates
Online08 Oct 2021
Publication process dates
Completed18 Nov 2021
Deposited01 Mar 2024
Place of publicationTurkey
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