Lecture 6: Network Analysis

Social media networks grow rapidly. Business, especially marketing folks, want to utilize Big Data to distribute customized message to potential customers. People want to connect to each other to strengthen their individual social networks, building relationship. To achieve those objectives, more and more demand of networks analysis increase. To do network analysis, first we should think about what kind of network we are going to construct and what are we going to define node in the network. Then, how do we connect those nodes? Social media connect people as nodes. This post will focus on two current popular social media in the United States: LinkedIn and Tweeter.

LinkedIn is a professional social media, allowing users to upload resume and connect to each other in related fields.
A special application of LinkedIn is LinkedIn InMaps (inmaps.linkedinlabs.com/). Inmaps graphically shows how your own networks looks like, using distinct colors and clusters to group your social networks. We can observe the structure of InMaps to recognize the density or degree of the relationship, growing networks. By tracking the map over time, we can see our behavior and how we build network.

Example of InMaps: My InMaps

  

Second, Tweeter is a short message posting social media, allowing people to follow others. The most obvious difference between LinkedIn and Tweeter is that Tweeter show the direction of relationship among people by indicating followed or following. Interactions among people are also easily to see by observing tweet and retweet. Users use hashtags to show a group discussion for people in the group easily to find the thread. A lot of data are out there. How to retrieve useful information from data is a critical issue, so now several social media analysis websites are built, such as the Archivist (http://archivist.visitmix.com/), saving and analyzing tweets.

Example of Archivist: Search for "MIS587"