基于递归神经网络的卫生社会保障管理员情感分析

Faisal Faturohman, Budhi Irawan, C. Setianingsih
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引用次数: 0

摘要

推特是一种用于传达意见、交换信息、上传视频和照片的社交媒体。在社交媒体Twitter上,信息的交流正迅速成为一种优势,因此它经常被用于以批评和建议的形式传递新闻和意见,例如向政府机构,例如,每当出现增加社会保障管理员健康的问题时,它总是公众之间的意见之战。社会保障卫生管理局是一个政府机构,负责保障印度尼西亚人民的健康;在这种情况下,公务员和私营工人必须登记参加这种保险和穷人保险。就保险金增加问题,国民之间的舆论战将以肯定和否定的形式展开,并将利用循环神经网络(Recurrent Neural Network)分类方法建立情绪分析系统。从Twitter用户情绪分析的研究结果来看,该系统可以根据人们在Twitter社交媒体上的观点来分析意见,平均准确率为86.67%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis on Social Security Administrator for Health Using Recurrent Neural Network
Twitter is a social media used to convey opinions, exchange information, upload videos and photos. On social media Twitter, the exchange of information is fast becoming an advantage, so it is often used in delivering news and opinions in the form of criticism and suggestions such as to government agencies, for example, every time there is an issue of increasing dues to Social Security Administrator for Health, it is always a battle of opinion between the public. Social Security Administrator for Health is a government agency that guarantees the health of the Indonesian people; in this case, civil servants and private workers are required to register for this insurance and insurance for the poor. Opinion wars related to the issue of increasing insurance contributions between the public in the form of positive and negative opinions, a sentiment analysis system will be created using the Recurrent Neural Network classification method. This system can help analyze opinions based on people's perspectives on Twitter social media, from the research results in the sentiment analysis of Twitter users, with an average accuracy of 86.67%.
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