Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms
The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2023-12-01
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| Series: | Management Systems in Production Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/mspe-2023-0041 |
| _version_ | 1797397364819886080 |
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| author | Nurdin Tubagus Asep Alexandri Mohammad Benny Sumadinata Widya Arifianti Ria |
| author_facet | Nurdin Tubagus Asep Alexandri Mohammad Benny Sumadinata Widya Arifianti Ria |
| author_sort | Nurdin Tubagus Asep |
| collection | DOAJ |
| description | The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of public opinion and the direction of the debate regarding old and new fintech technologies. The results of the study show that the SVM algorithm has an average accuracy of 87.32% and the NB algorithm has an average accuracy of 81.56% in testing the sample data in a comparison of old and new fintech technology on the internet. The study tested data in a comparison of two specific arguments, namely the debate about which technology is more efficient in old and new fintech on the internet. Despite many unresolved arguments, the study successfully proved that new fintech is more preferred than old fintech, with 71% positive sentiment directed towards new fintech. However, the dataset also found that 62% negative sentiment is directed towards new fintech, indicating that although new fintech is more preferred, there are still some issues that need to be addressed. One reason for negative sentiment towards new fintech may be the continued concerns about security and privacy of user data. Furthermore, other factors that may cause negative sentiment towards new fintech include a lack of understanding about how the technology works. |
| first_indexed | 2024-03-09T01:08:49Z |
| format | Article |
| id | doaj.art-a0d0e1b908734e3aa1984a15f2cb5af4 |
| institution | Directory Open Access Journal |
| issn | 2450-5781 |
| language | English |
| last_indexed | 2024-03-09T01:08:49Z |
| publishDate | 2023-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Management Systems in Production Engineering |
| spelling | doaj.art-a0d0e1b908734e3aa1984a15f2cb5af42023-12-11T07:38:05ZengSciendoManagement Systems in Production Engineering2450-57812023-12-0131437338010.2478/mspe-2023-0041Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB AlgorithmsNurdin Tubagus Asep0Alexandri Mohammad Benny1Sumadinata Widya2Arifianti Ria31Institut Teknologi Tangerang Selatan2Padjadjaran University2Padjadjaran University2Padjadjaran UniversityThe aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of public opinion and the direction of the debate regarding old and new fintech technologies. The results of the study show that the SVM algorithm has an average accuracy of 87.32% and the NB algorithm has an average accuracy of 81.56% in testing the sample data in a comparison of old and new fintech technology on the internet. The study tested data in a comparison of two specific arguments, namely the debate about which technology is more efficient in old and new fintech on the internet. Despite many unresolved arguments, the study successfully proved that new fintech is more preferred than old fintech, with 71% positive sentiment directed towards new fintech. However, the dataset also found that 62% negative sentiment is directed towards new fintech, indicating that although new fintech is more preferred, there are still some issues that need to be addressed. One reason for negative sentiment towards new fintech may be the continued concerns about security and privacy of user data. Furthermore, other factors that may cause negative sentiment towards new fintech include a lack of understanding about how the technology works.https://doi.org/10.2478/mspe-2023-0041fintechsvmsentiment analysisnb |
| spellingShingle | Nurdin Tubagus Asep Alexandri Mohammad Benny Sumadinata Widya Arifianti Ria Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms Management Systems in Production Engineering fintech svm sentiment analysis nb |
| title | Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms |
| title_full | Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms |
| title_fullStr | Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms |
| title_full_unstemmed | Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms |
| title_short | Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms |
| title_sort | sentiment analysis of user preference for old vs new fintech technology using svm and nb algorithms |
| topic | fintech svm sentiment analysis nb |
| url | https://doi.org/10.2478/mspe-2023-0041 |
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