Word2vec and Clustering based Twitter Sentiment Analysis
- Resource Type
- Conference
- Authors
- Coban, Onder; Ozyer, Gulsah Tumuklu
- Source
- 2018 International Conference on Artificial Intelligence and Data Processing (IDAP) Artificial Intelligence and Data Processing (IDAP), 2018 International Conference on. :1-5 Sep, 2018
- Subject
- Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Twitter
Sentiment analysis
Dogs
Support vector machines
Computational modeling
Feeds
Data mining
Word2vec
Clustering
Text Representation
Sentiment Analysis
- Language
ÖzetçeHigh dimensionality of feature space is major problem due to the sentiment analysis is usually considered as text classification problem. In this study, we investigated the applicability of “word2vec and clustering based text representation” method for Twitter sentiment analysis. We conducted experiments on two different datasets that are comprised of Turkish Twitter feeds from which one is subject-dependent and the other one is subject-independent. In classification phase, we utilized Support Vector Machine (SVM) algorithm. Experimental results show that the W2VC has been quite successful and has provided a tremendous advantage in terms of time and performance as it reduces feature space, but it does not provide enough success in terms of accuracy.