Twitter sentiment analysis with a deep neural network: An enhanced approach using user behavioral information

摘要: Abstract Sentiment analysis on social media such as Twitter has become a very important and challenging task. Due to the characteristics of data—tweet length, spelling errors, abbreviations, special characters—the sentiment task in an environment requires non-traditional approach. Moreover, is fundamental problem with many interesting applications. Most current classification methods judge polarity primarily according textual content neglect other information these platforms. In this paper, we propose neural network model that also incorporates user behavioral within given document (tweet). The used paper Convolutional Neural Network (CNN). system evaluated two datasets provided by SemEval-2016 Workshop. proposed outperforms baseline models (including Naive Bayes Support Vector Machines), which shows going beyond (tweet) beneficial classification, because it provides classifier deep understanding