Sentiment, Semantics and Some Snapdeal: A Brief Discussion on the Usefulness of Sentiment Analysis

So I have a new post about Sentiment Analysis. Excerpt below.

“One person’s data is another person’s noise.”
―  K.C. Cole (Author of the Universe and the Teacup)

The last couples of weeks I have been discussing Social Media Monitoring and Listening in my social media lectures. With so much content being created and shared on social networks like Twitter, Facebook, Instagram, Pinterest and Linkedin, brands need to constantly listen for relevant conversations, words, and themes to inform them of the sentiment around their products, brands and the organization itself.The listening has to be calibrated according to the goal of course: if the goal is awareness then one way of measuring it would be to see how many people are using the name of the brand in conversations across social and to what extent is the conversation positive or negative. This is where sentiment analysis or opinion mining would fit in. Usually, considering the number of data points, sentiment analysis is performed by written programs. To perform it manually for 500 mn tweets sent out everyday would be humanly impossible. There is a range of tools available to track sentiment online…

Read the complete post on Linkedin.

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