An analysis of environmental big data through the establishment of emotional classification system model based on machine learning: focus on multimedia contents for portal applications

With the advent of the Internet, there have been many changes. As existing means of off-line communication have transferred to the Internet, a wide range of multimedia services are emerging. And unlike in the past, these work as tremendous sources from which people’s opinions and attitudes can be obtained. Particularly, diverse opinions and reviews posted on the web in real time help corporations or the State establish the directions of policies. In this context, this study developed machine learning-based environment issue sentiment classifier in order to find out, from comments posted below news, how people recognize issues about climate change in terms of environment. Based on training data constructed by this study, a sentiment classification algorithm was constructed by applying SVM (support vector machine) and Naive Bayes, which are machine learning techniques, and a sentiment classifier was constructed by applying CNN (convolutional neural networks) and Bi-LSTM (bidirectional long-short term memory) techniques among deep learning techniques recently researched vigorously; and then their performance was compared.