{"title":"基于卷积神经网络的在线交通服务情感分析","authors":"Donny Sabri Ashari, Budhi Irawan, C. Setianingsih","doi":"10.23919/eecsi53397.2021.9624261","DOIUrl":null,"url":null,"abstract":"Online transportation services are public transportation that is much in demand by the public. According to the We Are Social 2020 report, as many as 21.7 million people in Indonesia use online transportation services. Customers or consumers often channel their opinions and complaints through various media. One of them is social media Instagram. On Instagram, online transportation services have an official account to provide the latest information about the service and collect comments from the public. When examined further, the collection of comments can be used as a sentiment analysis system. When assembled, we will conclude an online transportation service that has the best sentiment on Instagram. Therefore, the system created can analyze sentiments on online transportation service products using the CNN (Convolutional Neural Network) method. This system is expected to help consumers of online transportation services choose the best service from sentiment analysis. The results of this thesis in classifying sentiments in the Instagram comments column managed to get an accuracy of an average of 94%.","PeriodicalId":259450,"journal":{"name":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sentiment Analysis on Online Transportation Services Using Convolutional Neural Network Method\",\"authors\":\"Donny Sabri Ashari, Budhi Irawan, C. Setianingsih\",\"doi\":\"10.23919/eecsi53397.2021.9624261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Online transportation services are public transportation that is much in demand by the public. According to the We Are Social 2020 report, as many as 21.7 million people in Indonesia use online transportation services. Customers or consumers often channel their opinions and complaints through various media. One of them is social media Instagram. On Instagram, online transportation services have an official account to provide the latest information about the service and collect comments from the public. When examined further, the collection of comments can be used as a sentiment analysis system. When assembled, we will conclude an online transportation service that has the best sentiment on Instagram. Therefore, the system created can analyze sentiments on online transportation service products using the CNN (Convolutional Neural Network) method. This system is expected to help consumers of online transportation services choose the best service from sentiment analysis. The results of this thesis in classifying sentiments in the Instagram comments column managed to get an accuracy of an average of 94%.\",\"PeriodicalId\":259450,\"journal\":{\"name\":\"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/eecsi53397.2021.9624261\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/eecsi53397.2021.9624261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
在线交通服务是大众非常需要的公共交通工具。根据《We Are Social 2020》报告,印尼有多达2170万人使用在线交通服务。顾客或消费者经常通过各种媒体表达他们的意见和投诉。其中之一就是社交媒体Instagram。在Instagram上,在线交通服务有一个官方账号,提供有关该服务的最新信息,并收集公众评论。当进一步检查时,评论的收集可以用作情感分析系统。组装完成后,我们将总结出一款Instagram上情绪最好的在线运输服务。因此,该系统可以使用CNN(卷积神经网络)方法分析在线交通服务产品的情绪。预计该系统将帮助在线交通服务消费者通过情感分析选择最佳服务。本文对Instagram评论栏中的情绪进行分类的结果达到了平均94%的准确率。
Sentiment Analysis on Online Transportation Services Using Convolutional Neural Network Method
Online transportation services are public transportation that is much in demand by the public. According to the We Are Social 2020 report, as many as 21.7 million people in Indonesia use online transportation services. Customers or consumers often channel their opinions and complaints through various media. One of them is social media Instagram. On Instagram, online transportation services have an official account to provide the latest information about the service and collect comments from the public. When examined further, the collection of comments can be used as a sentiment analysis system. When assembled, we will conclude an online transportation service that has the best sentiment on Instagram. Therefore, the system created can analyze sentiments on online transportation service products using the CNN (Convolutional Neural Network) method. This system is expected to help consumers of online transportation services choose the best service from sentiment analysis. The results of this thesis in classifying sentiments in the Instagram comments column managed to get an accuracy of an average of 94%.