SENTIMENT ANALYSIS OF INDONESIAN COMMUNITY TOWARDS ELECTRIC MOTORCYCLES ON TWITTER USING ORANGE DATA MINING

Zulham Sitorus, Maulian Saputra, Siti Nurhaliza Sofyan, Susilawati
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Abstract

This study explores sentiment analysis of the Indonesian community towards electric motorcycles on Twitter using Orange Data Mining. In the context of the increasing popularity of electric vehicles, especially electric motorcycles, understanding public sentiment becomes crucial for various stakeholders. Twitter, as a leading social media platform, serves as a rich source of opinions and discussions on various topics, including electric motorcycles. This research utilizes Orange Data Mining with multilingual sentiment analysis techniques to analyze the sentiment of the Indonesian community regarding electric motorcycles. The results of sentiment analysis are visualized through box plots and scatter plots, aiming to classify Twitter users based on their emotional responses. The findings of this study provide valuable insights into the sentiment landscape surrounding electric motorcycles in Indonesia, benefiting policymakers, manufacturers, and marketers in understanding public perception and making informed decisions.
利用橙色数据挖掘对印度尼西亚社区在 twitter 上对电动摩托车的情感分析
本研究利用 Orange 数据挖掘技术探讨了印度尼西亚社区对 Twitter 上电动摩托车的情感分析。在电动汽车(尤其是电动摩托车)日益普及的背景下,了解公众情绪对各利益相关方至关重要。推特作为一个领先的社交媒体平台,是各种话题(包括电动摩托车)的意见和讨论的丰富来源。本研究利用橙色数据挖掘和多语言情感分析技术来分析印尼社区对电动摩托车的情感。情感分析的结果通过方框图和散点图进行可视化,旨在根据用户的情感反应对 Twitter 用户进行分类。本研究的结果为了解印尼电动摩托车的情感状况提供了宝贵的见解,有助于政策制定者、制造商和营销人员了解公众的看法并做出明智的决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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