Hoax Detection Tweets of the COVID-19 on Twitter Using LSTM-CNN with Word2Vec

Abstract

The growth of Twitter users is increasing every year, impacting activities in social media such as hoaxes that are increasingly widespread on various platforms. During this pandemic, the rate of hoaxes is growing because nowadays, it is very easy for humans to interact with each other, have opinions, and exchange information. One of the hoaxes that often appears is the hoax about the Covid-19 virus. Therefore, a method for detecting hoaxes is needed, especially for the topic of the Covid-19 virus in Indonesia. The method used in hoax detection is LSTM-CNN with Word2Vec. More than 1000 tweets data are used in this study, divided into hoax and non-hoax categories. Detection is carried out to analyze the hoax results obtained by using Word2Vec as a method to convert data as a classification vector and LSTM-CNN to classify the data. This work's result showed that the LSTM-CNN model with Word2Vec achieves 79.71% accuracy, surpassing the LSTM model and CNN model.