Popularity Analysis on Social Network: A Big Data Analysis

A social network is a social structure made up of a set of social actors. These actors form a network of social interactions and personal relationships. These networks are a valuable source of information about the users. Thus, analyzing these social interactions (particularly from more popular social networks such as Twitter, Facebook, etc.) allow us to predict the interests of users from a common place, group, friend circle, etc. From a business point of view, it helps by analyzing the popularity of products that are so often advertised in social networks, by looking at how many users have visited the product page, or how many people have liked the product. In similar context, the popularity of a group or person can help conclude the result of certain events such as elections. This paper explores the popularity index of different politicians in Twitter using MapReduce. We focused on tracking mainly politicians. For each person, we have tracked a list of associated words and counted the frequencies that these words appear in tweets as well as number of followers.