PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks
Recognizing emotions is vital in communication. Emotions convey additional meanings to the communication process. Nowadays, people can communicate their emotions on many platforms; one is the product review. Product reviews in the online platform are an important element that affects customers’ buyi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-10-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922007612 |
| _version_ | 1828110987652235264 |
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| author | Rhio Sutoyo Said Achmad Andry Chowanda Esther Widhi Andangsari Sani M. Isa |
| author_facet | Rhio Sutoyo Said Achmad Andry Chowanda Esther Widhi Andangsari Sani M. Isa |
| author_sort | Rhio Sutoyo |
| collection | DOAJ |
| description | Recognizing emotions is vital in communication. Emotions convey additional meanings to the communication process. Nowadays, people can communicate their emotions on many platforms; one is the product review. Product reviews in the online platform are an important element that affects customers’ buying decisions. Hence, it is essential to recognize emotions from the product reviews. Emotions recognition from the product reviews can be done automatically using a machine or deep learning algorithm. Dataset can be considered as the fuel to model the recognizer. However, only a limited dataset exists in recognizing emotions from the product reviews, particularly in a local language. This research contributes to the dataset collection of 5400 product reviews in Indonesian. It was carefully curated from various (29) product categories, annotated with five emotions, and verified by an expert in clinical psychology. The dataset supports an innovative process to build automatic emotion classification on product reviews. |
| first_indexed | 2024-04-11T11:27:55Z |
| format | Article |
| id | doaj.art-2f6ffabeff6e44bc997f023d44a5a61d |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-11T11:27:55Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-2f6ffabeff6e44bc997f023d44a5a61d2022-12-22T04:26:14ZengElsevierData in Brief2352-34092022-10-0144108554PRDECT-ID: Indonesian product reviews dataset for emotions classification tasksRhio Sutoyo0Said Achmad1Andry Chowanda2Esther Widhi Andangsari3Sani M. Isa4Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11480 IndonesiaCorresponding author.; Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11480 IndonesiaComputer Science Department, School of Computer Science, Bina Nusantara University, Jakarta 11480 IndonesiaPsychology Department, Faculty of Humanities, Bina Nusantara University, Jakarta 11480 IndonesiaComputer Science Department, BINUS Graduate Program - Master of Computer Science, Bina Nusantara University, Jakarta 11480 IndonesiaRecognizing emotions is vital in communication. Emotions convey additional meanings to the communication process. Nowadays, people can communicate their emotions on many platforms; one is the product review. Product reviews in the online platform are an important element that affects customers’ buying decisions. Hence, it is essential to recognize emotions from the product reviews. Emotions recognition from the product reviews can be done automatically using a machine or deep learning algorithm. Dataset can be considered as the fuel to model the recognizer. However, only a limited dataset exists in recognizing emotions from the product reviews, particularly in a local language. This research contributes to the dataset collection of 5400 product reviews in Indonesian. It was carefully curated from various (29) product categories, annotated with five emotions, and verified by an expert in clinical psychology. The dataset supports an innovative process to build automatic emotion classification on product reviews.http://www.sciencedirect.com/science/article/pii/S2352340922007612Natural language processingText processingText miningEmotions classificationSentiment analysis |
| spellingShingle | Rhio Sutoyo Said Achmad Andry Chowanda Esther Widhi Andangsari Sani M. Isa PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks Data in Brief Natural language processing Text processing Text mining Emotions classification Sentiment analysis |
| title | PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks |
| title_full | PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks |
| title_fullStr | PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks |
| title_full_unstemmed | PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks |
| title_short | PRDECT-ID: Indonesian product reviews dataset for emotions classification tasks |
| title_sort | prdect id indonesian product reviews dataset for emotions classification tasks |
| topic | Natural language processing Text processing Text mining Emotions classification Sentiment analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922007612 |
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