Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings
This is an incremental contribution to the MediaEval 2022 FakeNews task, addressing misinformation detection in social media for public health applications.
The paper tackled the classification of COVID-19 conspiracy tweets by using BERT, ELMO, and their combination with RandomForest, finding that ELMO slightly outperformed BERT but their combination reduced performance.
The FakeNews task in MediaEval 2022 investigates the challenge of finding accurate and high-performance models for the classification of conspiracy tweets related to COVID-19. In this paper, we used BERT, ELMO, and their combination for feature extraction and RandomForest as classifier. The results show that ELMO performs slightly better than BERT, however their combination at feature level reduces the performance.