Before revision:  As strong concerns and emotions are expressed in the tweets, we analysed the tweets content using natural language processing techniques and machine-learning based algorithms, and inferred seventeen latent semantic attributes associated with each tweet, including 1)
After revision:  As strong concerns and emotions are expressed in the tweets, we analysed the tweets content using natural language processing techniques and machine-learning based algorithms, we annotated each public tweet with seventeen latent semantic attributes associated with each tweet, including 1)