Thanks to AI Builder in Microsoft Power Apps and Flow, now we have access to sentiment analysis,

Keyword extraction and Language detection inside Microsoft Flow is now available.

In this post, I am going to show how to do sentiment analysis inside Power Automate.

First What is sentiment Analysis and what sort of analysis we have inside AI Builder for text analytics.

Text Analytics

in Power Automate and Power Apps three analytics is available as sentiment analytics, keyword extraction, and Language detection as below

As you can see in the below picture in AI builder under Build we have these three modules.

In this example, I am going to show sentiment analytics. The first login to account with AI builder account, then click on the Build and then click on the sentiment analysis

Then the new windows show the main purpose of the sentiment analysis. As you can see in the below picture, the only option to use is on Microsoft Power Automate (flow).

Next, you able to see some hints about using it in the Microsoft power Automate

Note: For long Text, analyze each sentence, not the whole document

Note: Use the same language for a document not multiple languages in a document

Then click on the Use in a Flow,

IN the Power Automate ( make sure you are in the same environment), then click on the solution and then click on the New then Flow.

In the new flow, click on the When a new email arrives

then choose the folder as inbox and the subject as Hotel

Next search for the predict for CDS, and for the model choose the SentimentAnalysis model, Then for the text choose the Body Preview,

Next for the language choose the language you will have as it is en for me

In the next step,  we are going to store the result in one drive for example, that you can provide a specific name for the file using the Concat function. In this example, I use the Utcnow to get the current time and date and the file type that is Text file as .txt.

for the file content, I am going to use the sentence to put in the file, before creating it, just click on the run you had from the previous example

as you can see we have a sentence-level sentiment analysis and a global level. I am going to Concat both of them.

then after the run code you should see below text file in the onedrive.

The post Sentiment Analysis Application: Microsoft Power Automate, Power Apps and AI Builder appeared first on RADACAD.

Follow Source

The post Sentiment Analysis Application: Microsoft Power Automate, Power Apps and AI Builder appeared first on Microsoft Dynamics 365 Blog.

In the last Post, I will explain how to analyze a JSON file that has been generated in the Sentiment Analysis process .

some explanation, this is a JSON file that contains the sentiment analysis for the comments one traveler put on the hotel website as below

The suite was awesome. We did not have much interaction with the staff. We did sleep on the queen size sofa bed in the living room instead of the queen size bed in the actual bedroom due to the temperature. It was very hot and humid. The air conditioner in the living room does not cool off the bedroom. This suite is very close to shopping and dining. After each day of adventures, we would walk to dinner at different joints. I will stay here again when I return.

the JSON file is like below

{“predictionOutput”:{“result”:{“sentiment”:”mixed”,”documentScores”:{“positive”:0.64,”neutral”:0.05,”negative”:0.31},”sentences”:[{“sentiment”:”positive”,”sentenceScores”:{“positive”:1.0,”neutral”:0.0,”negative”:0.0},”offset”:0,”length”:22},{“sentiment”:”neutral”,”sentenceScores”:{“positive”:0.01,”neutral”:0.83,”negative”:0.16},”offset”:23,”length”:48},{“sentiment”:”neutral”,”sentenceScores”:{“positive”:0.0,”neutral”:1.0,”negative”:0.0},”offset”:72,”length”:134},{“sentiment”:”neutral”,”sentenceScores”:{“positive”:0.03,”neutral”:0.93,”negative”:0.04},”offset”:207,”length”:26},{“sentiment”:”negative”,”sentenceScores”:{“positive”:0.01,”neutral”:0.06,”negative”:0.93},”offset”:234,”length”:69},{“sentiment”:”positive”,”sentenceScores”:{“positive”:0.92,”neutral”:0.08,”negative”:0.0},”offset”:304,”length”:48},{“sentiment”:”neutral”,”sentenceScores”:{“positive”:0.02,”neutral”:0.96,”negative”:0.02},”offset”:353,”length”:73},{“sentiment”:”neutral”,”sentenceScores”:{“positive”:0.03,”neutral”:0.92,”negative”:0.05},”offset”:427,”length”:37}]}},”operationStatus”:”Success”,”error”:null}

The related JSON file allocate an overall score to the whole comment, then for each sentence, you can get a separate sentiment score, the result in the JSON format is not able to analyze, so I decided to use Power Query to solve this problem

First Open Power BI desktop and navigate to Power Query, import the JSON file, then load the data, click on the record to expand it and to see the record and list. Right-click on both of them and add them as a separate query.

Then click on the To Table, and expand the records to see the inside, finally, you should see the 7 rows of data with label positive, negative and neutral, and the two last columns for the offset and length of each sentence.

Now we need to add the original text to merge them together, import the text file, then use the dot separator and Transpose to make them as a table. Then use the Add Column and add index column, to both the Sentence query and the hotel comment. Then in the Home Tab click on the Merge columns and merge them based on the Index

The post Analyse the JSON File with Power Query appeared first on RADACAD.

Follow Source

The post Analyse the JSON File with Power Query appeared first on Microsoft Dynamics 365 Blog.

There are many usages of  AI Builder for Object detection, form processing, Binary Prediction, Text classification, business card Reader. However, besides them, there is another one that is available now in Power Automate. In this post, I am going to show you how to use this feature, for creating a process for automatically apply sentiment analysis and create an output file to store back to Onedrive and then clean the result using Power Query.

Power Automate

navigate to Power Automate 

login to the account you have AI Builder environment, Then under the solution, create a new flow with the trigger of “When a file is Created” in Onedrive

In the next step, you need to select the Predict to component from the Next Step action, in the model section please choose the SentimentAnalysisModel 

Then in the Request Payload section, you need to first click in the box, then write the below code

{“text”:””,”language”:”en”} (make sure the it is “)

new window chooses the Expression and clicks on the ” ” in front of the text and from the Dynamic Content, choose the File content.

now choose a new action, and select the Create file to send back the result to the Onedrive.

for the Folder path just choose the location you want to save, for the file name you can use the Expression box to create a simple name and type like

then in the File content select the ResponsePayload from Dynamic Content

Now just save the flow and test it you should upload a text file that has some comments like Hotel comment in the text format, then you need to run the flow.

below text can be a sample from hotel review

“The suite was awesome. We did not have much interaction with the staff. We did sleep on the queen size sofa bed in the living room instead of the queen size bed in the actual bedroom due to the temperature. It was very hot and humid. The air conditioner in the living room does not cool off the bedroom. This suite is very close to shopping and dining. After each day of adventures we would walk to dinner at different joints. I will stay here again when I return.”

Now a JSON file should created and you can use Power BI to analyze it in an easy way.

In the next post, I will explain how to analyze the result with Power Query.

see the full video from here

The post Automation of Sentiment Analysis using AI Builder appeared first on RADACAD.

Follow Source

The post Automation of Sentiment Analysis using AI Builder appeared first on Microsoft Dynamics 365 Blog.