Social media information can be defined as non-structured data: narratives, random facts, opinions, numbers, fabrications, fables all mixed together with abandon with unknown relationships among any of the data. So why is this useful?
When you ask a question in a survey, you often get what the subject thinks you want to hear. If you want to know what a person is really thinking, you might have to eavesdrop. A better way is to check blogs, facebook postings, forums, tweets, and the like to see what people are thinking. In a traditional survey all the data is about you, and you control the questions. In a social media search the hit rate for topics you want information on, like your brand or event, is a small minority of comments made. You might have to sort through a half million documents to get any useful information. You might get better data if you look through millions of documents. Where does this info come from?
There are data aggregators who are always on the prowl gathering information for rent. You can get raw data from the aggregators that you can then put into your analytics engine. You could also employ your own crawler to go through your documents, customer comments and the like to create the mass of unstructured data you want to understand. The objective would be to create an aggregation metric that might look at what people are saying about your brand, product or company. You might want to see how these comments change over time. You can use it to gage opinion on a marketing campaign or product launch. This sort of input can provide valuable input to the way you run your business.
This information is still just correlated events, not causality. To take the next step as to what to do with this information, perhaps it’s time to join the speakers. By analyzing the information you can find out where people are talking about you, not just what they’re saying. You might want to monitor or participate in more active places where you are being discussed. This will require some thought to make sure you don’t undermine the activity, but provide people already thinking about your company or product to get even more involved.
Analyzing social media is not an exact science but an iterative process that you will do some probing and testing to see what results might be useful. The major reason for this is the raw data. It’s not about you. It’s about everything. Some sliver of information might be interesting for you, most will not. You will build rule sets to apply against text to find something, and more rule sets as you get results that aren’t quite what your were looking for. You’ll end up creating structured data out of unstructured data. Why? Because you want to find actionable information. That is best done with structured information.
Once you’ve gotten your rule set refined so that you’re getting useful information from the mountain of data, you’ll need to decide how often you want to search the mountain, what kind of analytic queries to find new information in the same mountain and where to find new mountains of data to pursue. The results are extracted into a structured array of objects that might include potential leads or product interest. That’s where the gold resides. You turn your marketing engine on those results, and refine the process to begin again.
Big Data Perspectives 