Sentiment Analysis on Online Transportation Services Using Convolutional Neural Network Method

被引：0
作者：
Ashari, Donny Sabri [1 ]
Irawan, Budhi [1 ]
Setianingsih, Casi [1 ]
机构：
[1] Telkom Univ, Sch Elect Engn, Bandung, Indonesia
来源：
2021 8TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, COMPUTERSCIENCE AND INFORMATICS (EECSI) 2021 | 2021年
关键词：
Sentiment Analysis; Convolutional Neural Network (CNN); Instagram;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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%.
引用
收藏
页码：335 / 340
页数：6
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