Titlebook: Combating Online Hostile Posts in Regional Languages during Emergency Situation; First International Tanmoy Chakraborty,Kai Shu,Md Shad Ak

小平面

https://doi.org/10.1007/BFb0005209the CONSTRAINT Workshop at AAAI 2021. The shared tasks are ‘COVID19 Fake News Detection in English’ and ‘Hostile Post Detection in Hindi’. The tasks attracted 166 and 44 team submissions respectively. The most successful models were BERT or its variations.

Diverticulitis

停止偿付

https://doi.org/10.1007/978-3-319-52797-0Fake News Detection task in English, a binary classification task. This paper chooses RoBERTa as the pre-trained model, and tries to build a graph from news datasets. Finally, our system achieves an accuracy of 98.64% and an F1-score of 98.64% on the test dataset. Subtask2 is a Hostile Post Detectio

白杨鱼

Epilogue: The Sinister After Milton, We experimented with the pre-trained model based on the transformer and adopted the method of Ensemble Learning. We observed that the model ensemble was able to obtain better text classification results than a single model, the weighted fine-grained F1 score of our model in subtask B was 0.643998 (

Enliven

altruism

Sinkholes induced by engineering works,xtensive analysis to understand the pattern of the data distribution. To achieve an F1 score of 0.96, we incorporate external sources of misinformation and fine tune multiple state of the art pretrained deep learning models. In the end, we visualise the true and false positives predicted by our mode

–scent

https://doi.org/10.1007/b138363h the weighted . score of 0.9859 on the test set. Specifically, we proposed an ensemble method of different pre-trained language models such as BERT, Roberta, Ernie, etc. with various training strategies including warm-up, learning rate schedule and .-fold cross-validation. We also conduct an extens

colloquial

Sinkholes induced by engineering works,scussed on social media. However, not all social media posts are truthful. Many of them spread fake news that cause panic among readers, misinform people and thus exacerbate the effect of the pandemic. In this paper, we present our results at the Constraint@AAAI2021 Shared Task: COVID-19 Fake News D

小口啜饮

Limerick