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Data Mining Approaches for Sentiment Analysis in Online Social Networks (OSNs)

Data Mining Approaches for Sentiment Analysis in Online Social Networks (OSNs)
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Author(s): Praneeth Gunti (National Institute of Technology, Kurukshetra, India), Brij B. Gupta (National Institute of Technology, Kurukshetra, India) and Elhadj Benkhelifa (Staffordshire University, UK)
Copyright: 2022
Pages: 26
Source title: Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Source Author(s)/Editor(s): Brij B. Gupta (National Institute of Technology, Kurukshetra, India), Dragan Peraković (University of Zagreb, Croatia), Ahmed A. Abd El-Latif (Menoufia University, Egypt) and Deepak Gupta (LoginRadius Inc., Canada)
DOI: 10.4018/978-1-7998-8413-2.ch005

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Abstract

IoT technology and the widespread usage of public networking platforms and apps also made it possible to use data mining in extracting useful perspectives from unorganised knowledge. In the age of big data, opinion mining may be applied as a valuable way in order to classify views into various sentiment and in general to determine the attitude of the population. Other methods to OSA have been established over the years in various datasets and evaluated in varying conditions. In this respect, this chapter highlights the scope of OMSA strategies and forms of implementing OMSA principles. Besides technological issues of OMSA, this chapter also outlined both technical problems regarding its production and non-technical issues regarding its use. There are obstacles for potential study.

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