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UiPath and Python for Sentiment Analysis

Implementing Sentiment Analysis in UiPath and Python

Photo by Hitesh Choudhary on Unsplash Want

To implement sentiment analysis in UiPath, we will use the TextBlob library in Python. TextBlob is a Python library for processing textual data. It provides a simple API for common natural language processing tasks such as sentiment analysis, part-of-speech tagging, and noun phrase extraction.


Prerequisites

Before we begin, make sure that you have Python and the TextBlob library installed on your machine. You can install TextBlob using the following command:



pip install textblob

Steps

Here are the steps to implement sentiment analysis in UiPath:

  1. Create a new UiPath project or open an existing one.

  2. Add the Invoke Python Method activity to your workflow.

  3. In the Invoke Python Method activity properties, set the following values:

    • Language: Python

    • Function Name: analyze_sentiment

    • Function Parameters: text (String)

    • Output: score (Float)

Once you have created the workflow and configured the Invoke Python Method activity properties, continue with the next steps:

  • Click on the Import button and import the following Python script: pythonCopy code:

python
from textblob import TextBlob

def analyze_sentiment(text):
    blob = TextBlob(text)
    return blob.sentiment.polarity

This script defines a function called analyze_sentiment that takes a string parameter called text. The function uses the TextBlob library to analyze the sentiment of the text and returns a score between -1 and 1.

  • Save the script and close the editor.

  • In your UiPath workflow, add an activity that retrieves the text that you want to analyze. This could be a text file, a web page, or any other source of text data.

    • Open your UiPath project or create a new one.

      • From the Activities panel, select the activity that corresponds to the type of text you want to retrieve. Here are some examples:

        • If you want to read text from a file, select the Read Text File activity from the File category.

        • If you want to extract text from a PDF file, select the Read PDF Text activity from the PDF category.

        • If you want to scrape text from a web page, select the Data Scraping Wizard from the Web category.

        • If you want to retrieve text from an API, select the HTTP Request activity from the Web category.

      • Configure the activity to retrieve the text that you want to analyze. The configuration will depend on the type of activity that you selected.

        • For the Read Text File activity, you will need to specify the file path and encoding of the text file.

        • For the Read PDF Text activity, you will need to specify the PDF file path.

        • For the Data Scraping Wizard, you will need to navigate to the web page that contains the text you want to extract and select the elements that contain the text.

        • For the HTTP Request activity, you will need to specify the URL of the API and any required parameters or authentication.

      • Save and test your workflow to ensure that the text retrieval activity is working correctly.

        • Once you have retrieved the text, you can connect it to the input of the Invoke Python Method activity to perform sentiment analysis using the TextBlob library.

  • Connect the output of the text retrieval activity to the input of the Invoke Python Method activity.

  • In the Invoke Python Method activity, set the value of the text parameter to the text that you retrieved in the previous step.

  • Run the workflow. The Invoke Python Method activity will analyze the sentiment of the text using the TextBlob library and return a score between -1 and 1 in the score variable.

  • Depending on the score, you can use UiPath activities to perform different actions. For example, if the score is negative, you can send an email alert or create a task to follow up on the negative sentiment. If the score is positive, you can log the result or take any other action that you choose.

Conclusion

In this article, we have seen how to integrate UiPath with a natural language processing (NLP) tool to perform sentiment analysis in UiPath using the TextBlob library in Python. With sentiment analysis, you can automatically categorize text data as positive, negative, or neutral, and take actions based on the sentiment score. This can be useful in a variety of scenarios, such as social media monitoring, customer feedback analysis, and more. By combining UiPath and Python, you can create powerful automation workflows that can analyze and act on text data with ease.

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