A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis

Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China

(2020) Huwen Wang et al.   Cell Discovery

Top Concerns of Tweeters During the COVID-19 Pandemic: Infoveillance Study

(2020) Alaa Abd-Alrazaq et al.   JOURNAL OF MEDICAL INTERNET RESEARCH

The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users

(2020) Sijia Li et al.   International Journal of Environmental Research and Public Health

Predicting pulsar stars using a random tree boosting voting classifier (RTB-VC)

(2020) F. Rustam et al.   Astronomy and Computing

Sentiment analysis of nationwide lockdown due to COVID 19 outbreak: Evidence from India

(2020) Gopalkrishna Barkur et al.   Asian Journal of Psychiatry

Estimating and projecting air passenger traffic during the COVID-19 coronavirus outbreak and its socio-economic impact

(2020) Stefano Maria Iacus et al.   SAFETY SCIENCE

The COVID-19 social media infodemic

(2020) Matteo Cinelli et al.   Scientific Reports

Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media

(2020) Koyel Chakraborty et al.   APPLIED SOFT COMPUTING

Tweets Classification on the Base of Sentiments for US Airline Companies

(2019) Furqan Rustam et al.   Entropy

Deep Convolution Neural Networks for Twitter Sentiment Analysis

(2018) Zhao Jianqiang et al.   IEEE Access

Using deep neural network with small dataset to predict material defects

(2018) Shuo Feng et al.   MATERIALS & DESIGN

Semantic Pooling for Complex Event Analysis in Untrimmed Videos

(2017) Xiaojun Chang et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A comparative study of TF*IDF, LSI and multi-words for text classification

(2010) Wen Zhang et al.   EXPERT SYSTEMS WITH APPLICATIONS