Abstract
Due to the globalisation of the COVID-19 pandemic, and the expansion of social media as the main source of information for many people, there have been a great variety of different reactions surrounding the topic. The World Health Organization (WHO) announced in December 2020 that they were currently fighting an “infodemic” in the same way as they were fighting the pandemic. An “infodemic” relates to the spread of information that is not controlled or filtered, and can have a negative impact on society. If not managed properly, an aggressive or negative tweet can be very harmful and misleading among its recipients. Therefore, authorities at WHO have called for action and asked the academic and scientific community to develop tools for managing the infodemic by the use of digital technologies and data science. The goal of this study is to develop and apply natural language processing models using deep learning to classify a collection of tweets that refer to the COVID-19 pandemic. Several simpler and widely used models are applied first and serve as a benchmark for deep learning methods, such as Long Short-Term Memory (LSTM) and Bidirectional Encoder Representations from Transformers (BERT). The results of the experiments show that the deep learning models outperform the traditional machine learning algorithms. The best approach is the BERT-based model.
Highlights
The massive spread of the COVID-19 virus throughout the world in a very fast and uncontrolled manner has resulted in one of the most difficult crises that our society has faced in the last several decades
We explored several traditional machine learning algorithms and some more advanced deep learning techniques, such as Long Short-Term Memory (LSTM) [4] and Bidirectional Encoder Representations from Transformers (BERT) [5]
We present the three different deep learning approaches used in this work: MultiLayer Perceptron (MLP), LSTM and BERT
Summary
The massive spread of the COVID-19 virus throughout the world in a very fast and uncontrolled manner has resulted in one of the most difficult crises that our society has faced in the last several decades. The internet has made it possible to reach any country in the world in a matter of seconds, and social media has connected millions of people, who can express their feelings, concerns and thoughts with just a few clicks. Social media platforms such as Facebook and Twitter can be useful tools to communicate between family, friends and other groups of people, but they can be used as a tool to spread misinformation and hate. As González-Padilla and Tortolero-Blanco mention, the worst aspect of social media is the potential to disseminate erroneous, alarmist and exaggerated information that can cause fear, stress, depression and anxiety in people with or without underlying psychiatric illnesses
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