"Ways to stop Social Media and Sentiment Mining"

While looking at my Google Analytics account i came across a keyword search originated from Australia which was different from keywords that usually drive traffic to my blog. The keywords were the following :

"Ways to stop Social Media and Sentiment Mining"

I decided to write this post assuming that the person who submitted this search does not like the fact that machines are mining his points of view about people or products or "understand" to some point whether he/she feels happy or not.

Among the many interesting aspects of being a Data Miner is to explain to other people what a Data Miner does (this was also discussed by G Piatetsky - Shapiro if my memory serves me well). When asked, i sometimes say that i also "analyze emotions as these are expressed on the Web". At first people are very interested but after a short amount of time almost always the next responses go along these lines :

- Are you allowed to do this?

- Is this legal?

- Have you ever heard about Big Brother?

It's no big secret that emotions play a major role in our lives and drive our decisions. Many people start to realize that companies are already using Information Extraction and Data - Text Mining techniques to extract the things that we discuss about various products or people and better understand our behavior. I believe that the most important thing in this area is not just Sentiment Mining or in other words whether we feel positive or negative about a Person, Product or Brand but the ability of Analytics to extract our core values and analyze our emotions.

When applying Text Mining or a mixture of Data and Text Mining methods on -for example- Twitter, we are not only able to see the sentiment for a product. We can identify a user that is alone, feeling bored and watching television. We can form several hypotheses on whether users that survived from Cancer express more positive thoughts than other user groups (see Surviving Cancer, Happiness and Twitter), find what sort of lifestyle makes a CEO happy or whether a specific profession increases your chances of being single (see Twitter Analytics : Cluster Analysis reveals similar users). Cluster Analysis can also identify core values of people and what they want or what trying to avoid.

Some of the examples discussed above have a clear business value while others don't. The important fact however is that analysts now have data to analyze emotions and our responses on facts happening in our lives on a much deeper level. This information has not been available on this scale before.

Should we stop extracting these insights and how dangerous can these insights become?