ABSTRACT
In Chapter 9, we discussed the importance of location mining and the challenges we are faced with in extracting the accurate locations of social media users. In Chapter 10, we discussed our collection of TweetHood algorithms for extracting the location of Twitter users. In particular, we have described three methods that show the evolution of the algorithm currently used in TweetHood. These algorithms are as follows: (i) a simple majority algorithm with variable depth, (ii) k closest friends with variable depth, and (iii) fuzzy k closest friends with variable depth. We have also provided experimental results for the algorithms. In this chapter, we propose a semisupervised learning method for label propagation. This algorithm is called Tweecalization.
