This paper presents an analysis of different methods for collecting training data in order to train a machine learning classifier for misinformation detection.
This paper presents an initial analysis of scientific misinformation from research papers.
We propose a novel reinforcement learning framework for misinformation detection on Twitter. We release both code, data and pre-trained models.
We propose pre-trained language models for political Twitter data. We evaluate all models and report results. We release both data and pre-trained models.
We propose pre-trained language models for political Twitter data. We evaluate all models and report results. We release both data and pre-trained models.
We propose a novel language modeling for stance detection. We release both data and pre-trained models.
Worldwide displacement due to war and conflict is at all-time high. Unfortunately, determining if, when, and where people will move is a complex problem. This paper proposes integrating both publicly available organic data from social media and …
Curriculum analysis is attracting widespread interest in educational field. There are two main approaches: (i) human-based and (ii) text-based assessments. Although an evaluation by teachers and learners are widely used, it is inconvenient and …
Electroencephalogram (EEG) has been used in the domain of emotion recognition, especially during the experience from music stimulus. A number of works have been submitted with promising results in emotion prediction tasks. Unfortunately, the majority …