Sentiment Analysis Implementation For Detecting Negative Sentiment Towards Indihome In Twitter Using Bidirectional Long Short Term Memory
- Resource Type
- Conference
- Authors
- Hernandi, Muhammad Kemal; Wibowo, Suryo Adhi; Suyanto, Suyanto
- Source
- 2021 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT), 2021 IEEE International Conference on. :143-147 Jul, 2021
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Sentiment analysis
Analytical models
Social networking (online)
Conferences
Blogs
Communications technology
Artificial intelligence
Artificial Intelligence
sentiment analysis
BiL-STM
Twitter
Indihome
- Language
Sentiment analysis is the method of extracting opinions from texts written in human language. Sentiment analysis can be used to analyze and evaluate the customer experience of the services that have been provided. With easy access to social media, sentiment analysis can be applied from people's comments on social media. One of the social media that is suitable for sentiment analysis is Twitter. In this paper, we focus on negative sentiment detection using tweets on Twitter by Indihome consumers. The system is designed to apply sentiment analysis using the BiLSTM method. Using BiLSTM, the accuracy 88 % is achieved.