Due to the vivid explanation of our teacher， I had got a preliminary impression on social media. Just as the name implies,social media means that everyone of us can participate in spreading and sharing information,which breaks the old pattern of messages spreading.
We had learned a lot of notions of social media and how to analysis contents.From my perspective,the K-means clustering is the most appealing part.During the class ,we learned the basic notion of K-means clustering,and using vector space model and cosine similarity to calculate estimate the distance between documents.
The procedures of the algorithm are as follows:
1.Chosing K data points from all data points randomly,each of which stands for a centroid.
2.Allocating the other objects based on the distance to the central points.
3.Calculating the average of each cluster and getting the new centroids.
4.Repeating step 1-3 until the function is astringed.
Despect the fact that K-means clustering algorithm is of great use in data mining,it is effective only when it is used to handle numerical value data.
When it comes to data like colors,shapes,stripes ,it will be failed.
At last,I would like to say that "Social Media Analysis and Development" is a really interesting course,and I will definitely learn a lot of from it.
