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Smart city article details
| Title | Sentiment Analysis On Smart City Mobile Platform Based On Lexicon |
|---|---|
| ID_Doc | 48464 |
| Authors | Ependi U.; Muzakir A.; Wibowo A. |
| Year | 2023 |
| Published | 2023 1st IEEE International Conference on Smart Technology: Advances in Smart Technology for Sustainable Well-Being, ICE-SMARTec 2023 |
| DOI | http://dx.doi.org/10.1109/ICE-SMARTECH59237.2023.10461957 |
| Abstract | This study investigates the analysis of social media data from platforms such as Facebook, Twitter, Instagram, and application reviews, with a focus on Smart City mobile platforms. While the availability of public service-related data presents a promising opportunity for analysis, the complexities and nuances of language pose significant challenges. To overcome this, the study employs lexicon-based analysis and machine learning-based classifiers to examine sentiment on Smart City platforms using data from reviews on the Tangerang Live application. The results demonstrate that lexicon-based analysis accurately describes the weighting of each word, enabling a clear portrayal of sentiment distribution. Furthermore, sentiment results can serve as a foundation for labeling, as evidenced by the high accuracy of the random forest, k-nearest neighbors, and naive Bayes classifiers, achieving 84%, 72%, and 64% accuracy, respectively. Overall, this study offers valuable insights into sentiment analysis on Smart City platforms, which can inform future research in this area. © 2023 IEEE. |
| Author Keywords | lexicon; machine learning; sentiment analysis; smart city platform |
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