Public perception of the fifth generation of cellular networks (5G) on social media

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
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:Ansari, Dr Shuja and Abbasi, Dr Qammer and Imran, Professor Muhammad and Taylor, William and Sambo, Dr Yusuf and Zahid, Mr Adnan 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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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172865EPSRC DTP 16/17 and 17/18Tania GalabovaEngineering and Physical Sciences Research Council (EPSRC)EP/N509668/1Research and Innovation Services