SocialNetworks

Centrality and text analysis allow users to get more out of their social network data. Here’s how you can leverage them using R and Gephi.

Thanks to rapid advances in technology, large amounts of data generated on social networks can be analyzed with relative ease, especially for those who use the R programming language and Gephi.

Many social networks provide APIs that enable the development of apps that expand their functionalities and grant access to user data and insights. This article compares popular social media APIs and gives examples of how to use them.

Analysts have come to recognize social network data as a virtual treasure trove of information for sensing public opinion trends and groundswells of support. In this article, Toptal Engineer Elder Santos describes the techniques he employed for a proof-of-concept that effectively analyzed Twitter Trend Topics to predict, as a sample test case, regional voting patterns in the 2014 Brazilian presidential election.