Sentiment analysis

Sentiment analysis, also referred to as opinion mining, is an approach to natural language processing (NLP) that identifies the emotional tone behind a body of text. This is a popular way for organizations to determine and categorize opinions about a product, service, or idea.

You can measure online sentiment using sentiment analysis. Sentiment analysis often uses artificial intelligence to identify the emotional tone of an online mention such as social media posts. It's important because it can be used to monitor the feelings and opinions that people have about your brand

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Sentiment analysis is contextual mining of text which identifies and extracts subjective information in source material, and helping a business to understand the social sentiment of their brand, product or service while monitoring online conversations. However, analysis of social media streams is usually restricted to just basic sentiment analysis and count based metrics. This is akin to just scratching the surface and missing out on those high value insights that are waiting to be discovered. So what should a brand do to capture that low hanging fruit?

With the recent advances in deep learning, the ability of algorithms to analyse text has improved considerably. Creative use of advanced artificial intelligence techniques can be an effective tool for doing in-depth research. We believe it is important to classify incoming customer conversation about a brand based on following lines:

Key aspects of a brand’s product and service that customers care about. Users’ underlying intentions and reactions concerning those aspects. These basic concepts when used in combination, become a very important tool for analyzing millions of brand conversations with human level accuracy. In the post, we take the example of Uber and demonstrate how this works. Read On!

Text Classifier — The basic building blocks

Sentiment Analysis

Sentiment Analysis is the most common text classification tool that analyses an incoming message and tells whether the underlying sentiment is positive, negative our neutral. You can input a sentence of your choice and gauge the underlying sentiment by playing with the demo here.
Intent Analysis Intent analysis steps up the game by analyzing the user’s intention behind a message and identifying whether it relates an opinion, news, marketing, complaint, suggestion, appreciation or query.


Sentiment Analysis Benefits

  • Social Media Sentiment Analysis
  • Brand Experience Insights
  • Improve Customer Service
  • Multilingual Insights
  • News Trend Analysis


How sentiment analysis can benefit a company or organization?

Sentiment analysis helps companies communicate better with customers and develop more relevant messages. By identifying the users' emotions, you can get a better idea of their experience and provide better customer service, which eventually leads to a decrease in customer churn

What is the objective of sentiment analysis?

The objective of sentiment analysis is to accurately extract people's opinions from a large number of unstructured review texts and classifying them into sentiment classes, i.e., positive, negative, or neutral. Sometimes “highly positive” and “highly negative” are also considered

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