Coronavirus (COVID-19) Global Sentiment Trend

This dataset gives a cursory glimpse at the overall sentiment trend of the public discourse regarding the COVID-19 pandemic on Twitter. The live scatter plot of this dataset is available as The Overall Trend block at https://live.rlamsal.com.np. The trend graph reveals multiple positive peaks and negative peaks that need to be further studied. The n-grams on those peaking and dropping periods can prove beneficial for better understanding the discourse.The dataset will be updated weekly and will continue until the development of the Coronavirus (COVID-19) Tweets Dataset is ongoing.What's inside the dataset files?Tweets collected every 10 minutes are sampled together, and an average sentiment score is computed. This dataset contains TXT files, each with two columns: (i) date/time and (ii) average sentiment. The first column is date/time and is by default in Unix timestamp (in ms). You can use this formula =cell/1000/60/60/24 + DATE(1970,1,1) in Spreadsheets, or this pd.to_datetime(dataframe_name[column],unit='ms') if you're comfortable with Python, to convert the Unix timestamp to human-readable format.