Indonesia's Fake News Detection using Transformer Network
원문 초록
Fake news is a problem faced by society in this era. It is not rare for fake news to cause provocation and problem for the people. Indonesia, as a country with the 4th largest population, has a problem in dealing with fake news. More than 30% of rural and urban population are deceived by this fake news problem. As we have been studying, there is only few literatures on preventing the spread of fake news in Bahasa Indonesia. So, this research is conducted to prevent these problems. The dataset used in this research was obtained from a news portal that identifies fake news, turnbackhoax.id. Using Web Scrapping on this page, we got 1116 data consisting of valid news and fake news. The dataset can be accessed at https://github.com/JibranFawaid/turnbackhoax-dataset. This dataset will be combined with other available datasets. The methods used are CNN, BiLSTM, Hybrid CNN-BiLSTM, and BERT with Transformer Network. This research shows that the BERT method with Transformer Network has the best results with an accuracy of up to 90%.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
DCR: Quantifying Data Contamination in LLMs Evaluation
The kernel of graph indices for vector search
Model-Based Real-Time Pose and Sag Estimation of Overhead Power Lines Using LiDAR for Drone Inspection
PocketVina Enables Scalable and Highly Accurate Physically Valid Docking through Multi-Pocket Conditioning
SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Step-by-step Instructions and a Simple Tabular Output Format Improve the Dependency Parsing Accuracy of LLMs
토론
이 논문과 연결된 포럼 글이 아직 없습니다.