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Public Perception of the Fifth Generation of Cellular Networks (5G) on Social Media

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 us...

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Detalles Bibliográficos
Autores principales: Dashtipour, Kia, Taylor, William, Ansari, Shuja, Gogate, Mandar, Zahid, Adnan, Sambo, Yusuf, Hussain, Amir, Abbasi, Qammer H., Imran, Muhammad Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259739/
https://www.ncbi.nlm.nih.gov/pubmed/34240048
http://dx.doi.org/10.3389/fdata.2021.640868
Descripción
Sumario: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.