Đăng nhập
 
Tìm kiếm nâng cao
 
Tên bài báo
Tác giả
Năm xuất bản
Tóm tắt
Lĩnh vực
Phân loại
Số tạp chí
 

Bản tin định kỳ
Báo cáo thường niên
Tạp chí khoa học ĐHCT
Tạp chí tiếng anh ĐHCT
Tạp chí trong nước
Tạp chí quốc tế
Kỷ yếu HN trong nước
Kỷ yếu HN quốc tế
Book chapter
Bài báo - Tạp chí
243 (2021) Trang: 52-58
Tạp chí: Lecture Notes in Networks and Systems

The sentiment dictionary plays an important role in analyzing or identifying opinion of users. A Sentiment dictionary is widely applicable to many different domains. Therefore, many researchers are interested in and building sentiment dictionaries. However, most of these dictionaries were built based on Vietnamese lexicon, when applied to social reviews often have low accuracy, because of the way social media is used different from Vietnamese lexicon. In this paper, we present a methodology of constructing Vietnamese sentiment dictionary with scoring for analyzing opinion of social reviews. We used training set with 5,200 labeled sentences that were collected from customer’s reviews about electronic product domain on electronic commerce websites. After that, we extracted nouns, adverbs and adjectives and then applied support measurement to calculate weight of them. The experimental results with 249 sentences have an accuracy of approximately 92% compared to 87% of dictionary that is developed based on Vietnamese lexicon, showing that our dictionary has a higher accuracy when applied to social sentiment analysis.

 
Các bài báo khác
Tập 55, Số 3 (2019) Trang: 9-17
Tải về
(2020) Trang: 237-244
Tạp chí: The 3rd International Conference on Sustainable Agriculture and Environment, Nong Lam University Ho Chi Minh City, November 18, 2020
7(2) (2016) Trang: 362-366
Tạp chí: (IJACSA) International Journal of Advanced Computer Science and Applications
 


Vietnamese | English






 
 
Vui lòng chờ...