Abstract
This study intents to provide an overview of the use of online digital news as a text dataset for future data analysis. Systematic literature review used as the method for collecting and analyze the information from previous study that used online digital news as a dataset. The result showed that the used of online digital news as a dataset can be implemented for classification and clustering. Furthermore, online digital news dataset is used to predict stock price and product price movement, to predict the approval rate for election process, to analyze the diseases epidemiology, to detect event, classification of fakes news, popularity of news in social media and other NLP tasks. By comparing online digital news dataset versus social media dataset, it can be used to detect fake news, news popularity prediction, stock price prediction, topic detection, sentiment analysis, event detection and prediction, spam detection, trending topic prediction and other task. Online digital news as a text dataset has a powerful performance to be implemented in the various field such as economics, political, health, language and so forth.
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