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Sentiment classification of unstructured data using lexical based techniques
Nurul Fathiyah Shamsudin1, Halizah Basiron2, Zurina Saaya3, Ahmad Fadzli Nizam Abdul Rahman4, Mohd Hafiz Zakaria5, Nurulhalim Hassim6.
Sentiment analysis is the computational study of people’s opinion or feedback, attitudes, and emotions toward entities, individuals, issues, events, topics and their attributes. There are many research conducted for other languages such as English, Spanish, French, and German. However, lack of research is conducted to harvest the information in Malay words and structure them into a meaningful data. The objective of this paper is to introduce a lexical based method in analysing sentiment of Facebook comments in Malay. Three types of lexical based techniques are implemented in order to identify the sentiment of Facebook comments. The techniques used are term counting, term score summation and average on comments. The comparison of accuracy, precision and recall for all techniques are computed. The result shows that the average on comments method outperforms the other two techniques.
Affiliation:
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
- Universiti Teknikal Malaysia Melaka, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q3 (Engineering (all)) |
Additional Information |
SJR (0.191) |
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