arXiv:1907.03167
Exploring difference in public perceptions on HPV vaccine between gender groups from Twitter using deep learning
원문 초록
In this study, we proposed a convolutional neural network model for gender prediction using English Twitter text as input. Ensemble of proposed model achieved an accuracy at 0.8237 on gender prediction and compared favorably with the state-of-the-art performance in a recent author profiling task. We further leveraged the trained models to predict the gender labels from an HPV vaccine related corpus and identified gender difference in public perceptions regarding HPV vaccine. The findings are largely consistent with previous survey-based studies.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins
Cautious Next Token Prediction
Where, What, Why: Towards Explainable Driver Attention Prediction
Out-of-Distribution Semantic Occupancy Prediction
Demystifying Distributed Training of Graph Neural Networks for Link Prediction
Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
토론
이 논문과 연결된 포럼 글이 아직 없습니다.