Social media sentiment analysis on Twitter using Suppoart Vector Machine (SVM) case study: KPK vs POLRI

S., Fatimah Ilona Asa (2015) Social media sentiment analysis on Twitter using Suppoart Vector Machine (SVM) case study: KPK vs POLRI. Diploma thesis, Universitas Al Azhar Indonesia.

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Abstract

Social media is a group of applications that allow people to give their opinion about interesting things to the public. The advantage of social media is the enormous amount of opinions that can be collected in a short time. For example, how people react to a certain issue and their loyalty to a certain side of that issue can lead the related parties to take the best strategy to respond. In addition, grouping people and their sentiments toward a party is the topic that will be explored in this study. The case study that is used is the rivalry between KPK and POLRI in early 2015. Before data mining was done, the researcher did some pre-processing phases and feature extraction. These phases translated raw data (tweets) to numerical data. Besides, support vector machine is used in this research to handle many data with many attribute. It was proved by the result of cross-validation that provides accuracy of 86,124%. Data visualization provides information about people tendency to side one or both parties and their sentiment that classified as positive or negative

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