Sentiment Analysis

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Richard Kershaw
Richard Kershaw creates websites for webmasters. He's the head honcho at Digital.com, and runs many other sites under the Quality Nonsense umbrella.

Last Updated on April 20, 2017

What Is Sentiment Analysis?

Sentiment analysis (also known as opinion mining) refers to the use of natural language processing, text analysis, and computational linguistics to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service Wikipedia

 

How Do We Use It

Every day, millions of people share their opinions on Twitter. They share their reviews about companies that offer small business tools, software, and products for running or growing a website

We monitor and use these micro-reviews and apply sentiment analysis to them to discover the positive and negative sentiments about those reviews.

In other words, we give you reviews that are powered by real people’s opinions on Twitter.

ratings

We like to think that you care about what other people think about a product, the same product that you are in the process of researching and evaluating.

What others think may help you decide whether or not you should purchase the product, tool, or software.

 

How It Works

We apply a sentiment analysis algorithm to the public tweets, and this algorithm determines if the tweet is positive or negative (or neutral, which we exclude).

This allows us to work out a score (an approval rating, if you like) of how many people like or dislike a company.

We use this simple formula: positive tweets divided by positive tweets plus negative tweets (# Total Positive Tweets / (# Total Positive Tweets + # Total Negative Tweets).