Update README.md

README.md

@@ -1,4 +1,4 @@
-# Sentiment Analysis of English Tweets (including COVID-19 specific tweets) with BERTsent
+# Sentiment Analysis of English Tweets (including COVID-19-specific tweets) with BERTsent
 
 **BERTsent**: A finetuned **BERT** based **sent**iment classifier for English language tweets.
 
@@ -10,11 +10,24 @@ Output labels:
  - 1 represents "neutral" sentiment
  - 2 represents "positive" sentiment
  
- ## COVID-19 tweets specific tasks
+ ## COVID-19 tweets specific task
  
  Eg.,
  The model distinguishes: "covid" -> neutral sentiment, "I have covid" -> negative sentiment
 
+## Cite
+
+If you use BERTsent in your project/research, please cite the following article:  
+Lamsal, R., Harwood, A., & Read, M. R. (2022). [Twitter conversations predict the daily confirmed COVID-19 cases](https://arxiv.org/abs/2206.10471). arXiv preprint arXiv:2206.10471.
+
+@article{lamsal2022twitter,    
+        title={Twitter conversations predict the daily confirmed COVID-19 cases},    
+        author={Lamsal, Rabindra and Harwood, Aaron and Read, Maria Rodriguez},    
+        journal={arXiv preprint arXiv:2206.10471},    
+        year={2022}        
+}
+
+
 ## Using the model
 
 Install transformers and emoji, if already not installed:
@@ -55,10 +68,4 @@ We have installed and imported everything that's needed for the sentiment analys
 Output: 
 
     [[0.972672164440155  0.023684727028012276 0.003643065458163619]]
-    0
-    
-If you use BERTsent in your project/research, cite the following article:
-    
-Lamsal, R., Harwood, A., & Read, M. R. (2022). [Twitter conversations predict the daily confirmed COVID-19 cases](https://arxiv.org/abs/2206.10471). arXiv preprint arXiv:2206.10471.
-
-
+    0