Analyze the Sentiment of Tweets and Reviews.

As more and more content is created and shared online through Social Channels, Blogs, Review Sites etc. the need and desire for businesses to mine this information, in order to gain business insight from it, has also increased.

Businesses try to unlock the hidden value of text in order to understand their customers’ opinions and needs and make better, more informed, business decisions. Traditionally, businesses relied on surveys, workshops and focus groups to gain insight into their customers opinions and feelings, but today with modern technology, we are able to harness the power of Machine Learning and Artificial Intelligence to extract meaning from text.

Detect sentiment of a document in terms of polarity (positive or negative) and subjectivity (subjectiveor objective).

Sentiment Analysis Image

Sentiment Analysis Example:

Let’s say we want to analyze a tweet, to figure out if it is positive, negative or neutral and whther it’s subjective or objective.

Sample Tweet:

“Literally ur facebook message app is useless, you only want it to increase profit. Please fix yourself. Its sad 
    GET /sentiment?text="Literally ur facebook message app is useless, you only want it to increase profit. Please fix yourself. Its sad "

Sentiment Analysis Results