Sentiment Analysis on Twitter data with Semi-Supervised Doc2Vec

被引：0
作者：
Bilgin, Metin [1 ]
Senturk, Izzet Fatih [1 ]
机构：
[1] Bursa Tech Univ, Fac Nat Sci Architecture & Engn, Bursa, Turkey
来源：
2017 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ENGINEERING (UBMK) | 2017年
关键词：
Semi-Supervised Learning; Doc2Vec; Sentiment Analysis; Machine Learning; Natural Language Processing;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
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.
引用
收藏
页码：661 / 666
页数：6
相关论文
共 21 条
  • [1] Sentiment analysis with Twitter
    Akgul, Eyup Sercan
    Ertano, Caner
    Diri, Banu
    [J]. PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2016, 22 (02): : 106 - 110
  • [2] [Anonymous], C EMP METH NAT LANG
  • [3] [Anonymous], INT WORKSH SMART HLT
  • [4] [Anonymous], 2011, J COMPUT SCI-NETH, DOI DOI 10.1016/j.jocs.2010.12.007
  • [5] Asur S., 2010, IEEE WIC ACM INT C W
  • [6] Cetin Mahmut, SIU 2013
  • [7] Claster WB, 2010, 2 WORLD C NAT BIOL I
  • [8] Ero ul U., 2009, THESIS
  • [9] Go Alec., 2009, Entropy, V17
  • [10] im ek M, 2012, 6 INT C APPL INF COM
123