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- W3091710326 abstract "Politic is one of the most favorite topics to discuss in social media for people in Indonesia. It was proven when a people movement to support the Commission of Corruption Eradication (KPK) named #SaveKPK has been enlived for ten years and become a trending topic on Twitter for several times. In this research, all tweets contain `#SaveKPK' are crawled and compiled using an alternative algorithm to get twitter historical data instead of using Twitter API. The result described the characteristic of the dataset statistically, from the most frequently used words to the most active users. A clustering algorithm named Latent Dirichlet Allocation (LDA) was run over the gathered text dataset to discover most relevant keywords using unsupervised learning approach." @default.
- W3091710326 created "2020-10-08" @default.
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- W3091710326 date "2020-08-01" @default.
- W3091710326 modified "2023-10-13" @default.
- W3091710326 title "Ten-Year Compilation of #SaveKPK Twitter Dataset" @default.
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- W3091710326 doi "https://doi.org/10.1109/icimtech50083.2020.9211246" @default.
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