To the world of social networking

Hello world! First blog post about this course and this blogger.

After attending first few lecture talks, I can feel the power and the potential of studying social networking. It is amazing that people invent intrinsic ways to analyze and model User Generated Contents by using Natural Language Processing and probability theory.

Actually, I am really interest on how modern social medias like facebook, google plus analyze user's behavior and how to make use of such kind of data to do advertisements pushing and promotions efficiently.

What I learnt from lecture 3 allows me to analyze users' content. Conceptually, by using term weighting, we are able to convert data from text based context to digits. Then, by using either or both of the vector space model and k-clustering, we are able to classify the type of the user context. Once we are able to categorize type of content, the remaining stuff is simply coding.

k-cluster

Besides the implementations, I am really excited about tricks on improving the accuracy of the classifications and how can those big companies profit from them. Hopefully, the following lectures will cover those issues one by one.