Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings

2023-03-07 · Abdul Rehman, Rabeeh Ayaz Abbasi, Irfan ul Haq Qureshi, Akmal Saeed Khattak

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.

📄 PDF Abstract BibTeX arXiv:2303.03706

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Tasks

Word Embeddings

Methods 이 논문이 사용한 방법론

Attention 설명 없음

Tanh Activation 설명 없음

Sigmoid Activation 설명 없음

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

LSTM An LSTM is a type of recurrent neural network that addresses the vanishing gradient problem in vanilla…

Multi-Head Attention 설명 없음

WordPiece 설명 없음

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

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