Dashtipour, K., Taylor, W. , Ansari, S. , Gogate, M., Zahid, A., Sambo, Y. , Hussain, A., Abbasi, Q. H. and Imran, M. A. (2021) Public perception of the fifth generation of cellular networks (5G) on social media. Frontiers in Big Data, 4, 640868. (doi: 10.3389/fdata.2021.640868)
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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.
Item Type: | Articles |
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Additional Information: | This research was funded under EPSRC DTA studentship (EPSRC DTG EP/N509668/1 Eng |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Sambo, Dr Yusuf and Ansari, Dr Shuja and Imran, Professor Muhammad and Zahid, Mr Adnan and Abbasi, Professor Qammer and Taylor, William and Dashtipour, Dr Kia |
Creator Roles: | Dashtipour, K.Conceptualization, Formal analysis Taylor, W.Conceptualization, Investigation, Resources, Writing – review and editing Ansari, S.Conceptualization, Formal analysis, Investigation Zahid, A.Conceptualization Sambo, Y.Conceptualization, Formal analysis Abbasi, Q.Conceptualization, Resources, Writing – review and editing, Funding acquisition Imran, M.Conceptualization, Resources, Writing – review and editing, Funding acquisition |
Authors: | Dashtipour, K., Taylor, W., Ansari, S., Gogate, M., Zahid, A., Sambo, Y., Hussain, A., Abbasi, Q. H., and Imran, M. A. |
College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
Journal Name: | Frontiers in Big Data |
Publisher: | Frontiers Media |
ISSN: | 2624-909X |
ISSN (Online): | 2624-909X |
Copyright Holders: | Copyright © 2021 The Authors |
First Published: | First published in Frontiers in Big Data 4:640868 |
Publisher Policy: | Reproduced under a Creative Commons License |
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