TWITTER DATA MINING FOR SENTIMENT ANALYSIS ON PEOPLES FEEDBACK AGAINST GOVERNMENT PUBLIC POLICY
DOI:
https://doi.org/10.20319/mijst.2017.31.110122Keywords:
Text Mining, Text Preprocessing, Twitter, Nazief and Adriani Algorithm, Public PolicyAbstract
Government policies often get positive or negative response from the public. The response from the community feedback can be conveyed through print and electronic media. With the rise of social media today, people have a tendency to convey such feedback through social media such as Facebook, Twitter, Instagram, Path and other social media. Thus, to determine the public response to this policy that has been implemented, the government needs to know how your feedback from people who come from social media. But because of the feedback, it is difficult to detect how many positive or negative response from the public. Therefore, in this study will develop a system to obtain data in the form of feedback coming from one of the social media that is often used by the public, namely Twitter. Tweet or post on the community will be collected based on the time and place specified. Having obtained a collection tweet, would do next text preprocessing stage. Tweet text already passed the stage of preprocessing, for further processing in sentiment analysis, to determine the positive and negative responses from the public against government policies that have been applied.
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