Sentiment Analysis on Twitter data with Semi-Supervised Doc2Vec
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Twitter is one of the most popular microblog sites developed in recent years. Feelings are analysed on the messages shared on Twitter so that users ideas on the products and companies can be determined. Sentiment analysis helps companies to improve their products and services based on the feedback obtained from the users through Twitter. In this study, it was aimed to perform sentiment analysis on Turkish and English Twitter messages using Doc2Vec. The Doc2Vec algorithm was run on Positive, Negative and Neutral tagged data using the Semi-Supervised learning method and the results were recorded.
Açıklama
2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEY
Anahtar Kelimeler
Semi-Supervised Learning, Doc2Vec, Sentiment Analysis, Machine Learning, Natural Language Processing
Kaynak
2017 International Conference On Computer Science And Engineering (Ubmk)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
