Sentiment Analysis
One of the standout applications of Natural Language Processing is Sentiment Analysis, a technique designed to discern and analyze the emotional tone expressed in textual data. Sentiment Analysis goes beyond mere language processing; it dives into the realm of understanding sentiments—whether positive, negative, or neutral—embedded in written expressions. This invaluable tool finds relevance across diverse industries, aiding businesses in gauging customer feedback, measuring public opinion on social media, and making data-driven decisions. As we navigate the digital landscape, Sentiment Analysis emerges as a pivotal component in unraveling the intricacies of human communication, offering insights that go beyond the surface of mere words.
Steps
In NLP & NLG section within PredictEasy.
Select the Sentiment Analysis option within the NLP & NLG tools.
Identify the independent variable (X) containing the text data for sentiment analysis.
Define the output column where you want the sentiment analysis results to be displayed.
Initiate the sentiment analysis process by clicking on the sentiment button.
Once the analysis is complete, you've indicated with positive, negative, and neutral sentiments along with the corresponding counts and also it is appended to next to each row.
Output:
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