Details

Autor(en) / Beteiligte

• Bhullar, Prabhdeep Kaur
• Vielma, Chary
• Bein, Doina
• Popa, Vlad

Titel

MeasureOP: Sentiment Analysis of Movies Text Data

Ist Teil von

• 16th International Conference on Information Technology-New Generations (ITNG 2019), p.557-562

Ort / Verlag

Cham: Springer International Publishing

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Sentiment analysis is a series of methods, techniques, and tools about detecting and extracting subjective information, such as opinion and attitudes, from language. The goal of our project was to classify movies’ reviews, by analyzing the polarity (positive or negative) of each paragraph in a review (Cui et al., Neurocomputing 187:126–132, 2016). We experimented with various RNN models on the Nervana Neon deep learning framework, an open-source framework developed by Nervana Systems, in order to improve accuracy in training and validation data. We experimented with network architecture, hyper parameters (batch size, number of epochs, learning rate, batch normalization, depth, vocabulary size) in order to find out which model works best for sentiment classification. This paper presents our findings and conclusions.