Open AccessSentiment Analysis of Movie Opinion in Twitter Using Dynamic Convolutional Neural Network Algorithm
Author(s) -
Fajar Ratnawati,
Edi Winarko
Publication year - 2018
Publication title -
indonesian journal of computing and cybernetics systems
Language(s) - English
Resource type - Journals
eISSN - 2460-7258
pISSN - 1978-1520
DOI - 10.22146/ijccs.19237
Subject(s) - convolutional neural network , sentiment analysis , naive bayes classifier , computer science , recall , value (mathematics) , precision and recall , measure (data warehouse) , artificial intelligence , social media , algorithm , natural language processing , machine learning , psychology , data mining , world wide web , support vector machine , cognitive psychology
Movie has unique characteristics. When someone writes an opinions about a movie, not only the story in the movie itself is written, but also the people involved in the movie are also written. Opinion ordinary movie written in social media primarily twitter.To get a tendency of opinion on the movie, whether opinion is likely positive, negative or neutral, it takes a sentiment analysis. This study aims to classify the sentiment is positive, negative and neutral from opinions Indonesian language movie and look for the accuracy, precission, recall and f-meausre of the method used is Dynamic Convolutional Neural Network. The test results on a system that is built to show that Dynamic Convolutional Neural Network algorithm provides accuracy results better than Naive Bayes method, the value of accuracy of 80,99%, the value of precission 81,00%, recall 81,00%, f-measure 79,00% while the value of the resulting accuracy Naive Bayes amounted to 76,21%, precission 78,00%, recall 76,00%, f-measure 75,00%.