text: All the hashtags in the tweets were automatically extracted with the Regular Expression Library 
  in Python. Hashtags were transformed to lowercase letters, and clear synonyms were stemmed 
  (e.g., #trump, #DonaldTrump, #donaldtrump). As all the tweets in the “climate change” dataset 
  contained the #climatechange hashtag and all the tweets in the “global warming” dataset contained the 
  #globalwarming hashtag, we did not document these two hashtags when processing data. The number 
  of hashtags contained in the two discourses in each year is displayed in Figure 1b. Hashtags whose 
  frequency was lower than ten times are excluded in the network analysis. As hashtags are intended 
  to be a topic anchor [52], extremely low frequency means that the hashtag is not recognized socially, 
  and excluding them helps researchers focus on meaningful rather than occasional associations. 
  
  3.3. Measurement 
  
  3.3.1. Hashtag Co-Occurrence Network 