New approch of opinion analysis from big social data environment using a supervised machine learning algirithm

Sentiment analysis is a very substantial area of research in our environment. Many studies have focused on the topic in recent years. It has rapidly gained interest due to the unusual volume of opinion-bearing data on the Internet (Big Social Data). In this paper, we focus on sentiment environment a...

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Bibliographic Details
Published in:E3S Web of Conferences 2021-01, Vol.319, p.1037
Main Authors: Saidi, Wiam, El Abderahmani, Abdellatif, Satori, Khalid
Format: Article
Language:English
Subjects:
Annotations
big social data
classification
Data mining
extraction
Learning algorithms
Machine learning
opinion mining
Sentiment analysis
Supervised learning
svm
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Summary:Sentiment analysis is a very substantial area of research in our environment. Many studies have focused on the topic in recent years. It has rapidly gained interest due to the unusual volume of opinion-bearing data on the Internet (Big Social Data). In this paper, we focus on sentiment environment analysis from Amazon customer reviews shared by a machine learning based approach. This process starts with the collection of reviews and their annotation followed by a text pre-processing phase in order to extract words that are reduced to their root. These words will be used for the construction of input variables using several combinations of extraction and weighting schemes. Classification is then performed by a supervised Machine Learning classifier. The results obtained from the experiments are very promising.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202131901037