Sentiment Analysis

Every day we create over 2.5 quintillion bytes of data. This is over 20000 times the size of the English text version of Wikipedia. This is information from Facebook statuses to Tweets to product reviews to millions of different things. Now say that you are a company and you want to find out the public opinion on something be it a product, a politician, or a medical procedure. It is not easy to have a person read the equivalent of 20,000 wikipedias to decide if people like something or not. And while much of this data is irrelevant, it is often very hard to know where to look for your data. And even if you do, if you know you want to look at every tweet in the last week and find the opinion on something, well searching every tweet made in the last week would still take more man power than most countries let alone businesses can provide.

Here comes sentiment analysis. Sentiment analysis is a technique that uses computers to analyze text to judge opinion. Your initial thought might be "Well, that shouldn't be too hard, and computers work a lot faster than people." You would be slightly right and slightly wrong. Getting computers to recognize a human concept just from the words used is a very hard task. A first approach would be to look for positive or negative words in relation to your product. But what if someone says "I would hate for someone to live without this product" or "If you enjoy pleasant day of sizzling the skin off your feet or eating food so lively that you get dysentery, this vacation spot is the place for you!" Sarcasm is a complex linguistic process that many humans fail to understand, let alone machines.

And yet this is what these computers do. They analyze text to judge public opinion and companies look at the results and make decisions based on what they find. These techniques are incredibly versatile and used in a myriad of ways in the electronic world.