From the course: Power BI: Integrating AI

Unlock this course with a free trial

Join today to access over 24,800 courses taught by industry experts.

Scoring language sentiment

Scoring language sentiment - Power BI Tutorial

From the course: Power BI: Integrating AI

Start my 1-month free trial Buy for my team

Scoring language sentiment

“

- [Narrator] When you read an email, read a comment, or engage in any type of written communication, there's more to the language than just the words and the phrases in the text itself. Language itself is imbued with meaning, whether we realize it or not. Text analytics is a pre-trained AI model using natural language processing with an extensive body of text with sentiment associations,. Let's say that we want to quantify our language by scoring its positive or negative tone. One way that we can do this is through the score sentiment AI model in the text analytics algorithms that we can run within Power BI. The score sentiment algorithm detects the overall positive or negative rating for written text as an outcome measured between the values of zero and one. Where a score close to zero indicates a negative tone and a score close to one indicates a positive tone. To test out how the score sentiment algorithm works, I created a few imaginary reviews as text prose in multiple paragraph…

Contents