원문정보
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초록
영어
Social media has become one of the most popular channels to keep updated with daily news because it can quickly and easily access information. This advantage is used by malicious people to spread fake news widely. Since the COVID-19 pandemic, fake news has become a huge social problem, causing people to panic and misunderstand how to cure or protect themselves from the virus. So, the goal of this research is to use deep learning as the Recurrent Neural Network (RNN) model to find fake news about COVID-19 in the Thai language on social media and help filter information by classifying real and fake news.
목차
ABSTRAC
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. Recurrent Neural Network (RNN)
2.2. Long Short-Term Memory (LSTM)
2.3. Gated Recurrent Unit (GRU)
2.4. Word2Vec
2.5. Related Works
Ⅲ. Method
3.1. Data Pre-processing
3.2. Model
3.3. Result
Ⅳ. Conclusion
Acknowledgments
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. Recurrent Neural Network (RNN)
2.2. Long Short-Term Memory (LSTM)
2.3. Gated Recurrent Unit (GRU)
2.4. Word2Vec
2.5. Related Works
Ⅲ. Method
3.1. Data Pre-processing
3.2. Model
3.3. Result
Ⅳ. Conclusion
Acknowledgments
저자정보
참고문헌
자료제공 : 네이버학술정보