Sentiment analysis on Twitter data with semi-supervised Doc2Vec


BİLGİN M. , ŞENTÜRK İ. F.

2017 International Conference on Computer Science and Engineering (UBMK), Turkey, 5 - 08 October 2017, pp.661-666 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ubmk.2017.8093492
  • Country: Turkey
  • Page Numbers: pp.661-666
  • Keywords: Semi-Supervised Learning, Doc2Vec, Sentiment Analysis, Machine Learning, Natural Language Processing

Abstract

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.