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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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| Published in: | E3S web of conferences 2021-01, Vol.319, p.1037 |
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| Language: | English |
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| container_title | E3S web of conferences |
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| creator | Saidi, Wiam El Abderahmani, Abdellatif Satori, Khalid |
| description | 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. |
| doi_str_mv | 10.1051/e3sconf/202131901037 |
| format | article |
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| language | eng |
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| subjects | Annotations big social data classification Data mining extraction Learning algorithms Machine learning opinion mining Sentiment analysis Supervised learning svm |
| title | New approch of opinion analysis from big social data environment using a supervised machine learning algirithm |
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