Kia Dashtipour
Public Perception of the Fifth Generation of Cellular Networks (5G) on Social Media
Dashtipour, Kia; Taylor, William; Ansari, Shuja; Gogate, Mandar; Zahid, Adnan; Sambo, Yusuf; Hussain, Amir; Abbasi, Qammer H.; Imran, Muhammad Ali
Authors
William Taylor
Shuja Ansari
Dr. Mandar Gogate M.Gogate@napier.ac.uk
Senior Research Fellow
Adnan Zahid
Yusuf Sambo
Prof Amir Hussain A.Hussain@napier.ac.uk
Professor
Qammer H. Abbasi
Muhammad Ali Imran
Abstract
With the advancement of social media networks, there are lots of unlabeled reviews available online, therefore it is necessarily to develop automatic tools to classify these types of reviews. To utilize these reviews for user perception, there is a need for automated tools that can process online user data. In this paper, a sentiment analysis framework has been proposed to identify people’s perception towards mobile networks. The proposed framework consists of three basic steps: preprocessing, feature selection, and applying different machine learning algorithms. The performance of the framework has taken into account different feature combinations. The simulation results show that the best performance is by integrating unigram, bigram, and trigram features.
Journal Article Type | Article |
---|---|
Acceptance Date | May 4, 2021 |
Online Publication Date | Jun 18, 2021 |
Publication Date | 2021 |
Deposit Date | Jul 22, 2021 |
Publicly Available Date | Jul 22, 2021 |
Journal | Frontiers in Big Data |
Print ISSN | 2624-909X |
Publisher | Frontiers Media |
Peer Reviewed | Peer Reviewed |
Volume | 4 |
Article Number | 640868 |
DOI | https://doi.org/10.3389/fdata.2021.640868 |
Keywords | sentiment analysis, 5G, mobile network quality, machine learning, opinion mining |
Public URL | http://researchrepository.napier.ac.uk/Output/2788415 |
Files
Public Perception Of The Fifth Generation Of Cellular Networks (5G) On Social Media
(1.1 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
© 2021 Dashtipour, Taylor, Ansari, Gogate, Zahid, Sambo, Hussain, Abbasi and Imran. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
You might also like
Toward's Arabic multi-modal sentiment analysis
(2018)
Presentation / Conference Contribution
A novel brain-inspired compression-based optimised multimodal fusion for emotion recognition
(2018)
Presentation / Conference Contribution
DNN driven speaker independent audio-visual mask estimation for speech separation
(2018)
Presentation / Conference Contribution
Deep learning driven multimodal fusion for automated deception detection
(2018)
Presentation / Conference Contribution
Exploiting Deep Learning for Persian Sentiment Analysis
(2018)
Presentation / Conference Contribution
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search