How do I format my data for a sentiment analysis task on Metaranx?
Sentiment analysis is a language task that requires text-based data. You will train your AI on text-based data and test/use it on text-based data. When you have completed this list, you will have a dataset prepared for building a sentiment analysis AI on Metaranx.
Open your preferred spreadsheet in preparation for entering your data (you can use Excel, Google Sheets, or any spreadsheet program that can export to a .CSV). Your dataset should be a maximum of 5MB.
Set up three columns
Column 1
Column 1 (or "A") needs to exist but remain blank
Column 1 (or "A") header/title remains blank
Column 2
Column 2 (or "B) needs to hold all your text-based data
Column 2 (or "B") does not require a header. Remove blank headers.
Add your data into rows, divided by their "label"
Column 3
Column 3 (or "C") needs to hold your labels
Column 3 (or "C") does not require a header. Remove blank headers.
Labels are between 1 and 10: for example all positive statements will be labeled as "0" and all negative statements will be labeled as "1" for a specific use case of positive versus negative sentiment detection. Your labels need to be consistent to their corresponding text, but can follow any pattern you choose.
How to structure your dataset
Add at least 1,000 rows per label with the goal to have 10,000 rows of data minimum
Export to a .CSV file
How to export your dataset from Google Sheets to .CSV.