Author: Qu, Z.; Ding, Z.
Title: Predicting the retweet level of covid-19 tweets with neural network classifier Cord-id: 5lbihhhh Document date: 2020_1_1
ID: 5lbihhhh
Snippet: A convolutional neural network (CNN) based classifier, to predict the retweet level of COVID-19 tweets, is proposed in this paper. The proposed CNN is able to predict whether a given COVID-19 tweet would be more retweeted, or less retweeted. The network is trained and validated with 100,000 and 5,000 English tweet samples, respectively, which were all posted within the last week of March 2020, and 81% accuracy has been achieved. The network is also evaluated by English tweet samples posted at th
Document: A convolutional neural network (CNN) based classifier, to predict the retweet level of COVID-19 tweets, is proposed in this paper. The proposed CNN is able to predict whether a given COVID-19 tweet would be more retweeted, or less retweeted. The network is trained and validated with 100,000 and 5,000 English tweet samples, respectively, which were all posted within the last week of March 2020, and 81% accuracy has been achieved. The network is also evaluated by English tweet samples posted at the end of April. The result shows that the accuracy is about 80%. Therefore, the proposed approach is robust and capable to process tweets of chosen contents/topics. ©2020 IEEE
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