Detect Sentiment Transformation: Determine the Sentiment of Text

Detect Sentiment Transformation: Determine the Sentiment of Text

This transformation works on a text (dimension) column and supports English text only. It processes non-English text as English and ignores images, including emoji. If the input value is null or an empty string (''), the transformation assigns the sentiment as Neutral or with a value of 2.5, depending on the output type. Applying Detect Sentiment on text such as IDs, nouns, addresses, or alphanumeric values) can return unexpected results.

1. In a Transform node of a Data Prep recipe, select the text (dimension) column that contains the text for sentiment analysis in the Preview tab.
2. In the Transform toolbar, click the Detect Sentiment button ().
   
3. Optionally, use More Options in the setup panel to change the output type or to show sentiment scores.
   

   Options	Description
   Output Type	Results of the sentiment analysis in a new column in the dataset. Text (default) shows detected sentiment as Positive, Neutral, or Negative. Number shows detected sentiment as a decimal value on a scale of from 1 through 5, with 5 as the most positive. When determining sentiment, Detect Sentiment classifies the text into groups from 1 through 5. When output is Text, the sentiment values are mapped to the numbers as follows: Positive is >3.50 and <= 5.00 Neutral is >= 2.50 and < 3.5 Negative is >= 1.00 and < 2.50 When output is Number, the sentiment is calculated as a weighted sum of the number probabilities.
   Show Sentiment Score	Einstein self-assesses its confidence in the accuracy of each sentiment option. Sentiment scores are decimal values that add up to 1 and that can be used in formulas. For example, trigger a support case when an online review is negative with a strong sentiment score. None (default) shows the detected sentiment column only. No sentiment scores are added to the dataset. All Sentiments shows the detected sentiment column and sentiment score columns in the dataset. If output type is Text, sentiment scores appear in three columns for Positive, Neutral, and Negative. If output type is Number, sentiment scores appear in five columns for 1, 2, 3, 4, and 5.

4. Optionally, to change the label of the column that stores the detected sentiments, go to Column Label.
5. To add the transformation to the Transform node, click Apply.

   The Preview tab shows the new sentiment column. The column shows the temporary value Sentiment TBD. To see the detected sentiment results, run the recipe.

   
6. To collapse the view and see the graph, click ().
7. Save the recipe.

After you run the recipe, you can view the detected sentiments in the sentiment column.