This article focuses on the problem of identifying influential Twitter users using Machine Learning (ML) techniques and Natural Language Processing (NLP).
The article aims to build an unsupervised model to estimate relationship strength based on profile similarity and interaction activity.
The authors of this article propose a methodology for automatically identifying events and their associated user-contributed social media documents (such as those posted on Flickr, YouTube, and Facebook) to enable event browsing and search in state-of-the-art search engines.
This 2012 article focuses on the detection of hidden relationship structures in online social networks including the characteristics of relationship structures on Facebook. The authors argue that graphs fail to capture the finer qualities of online social network relationships.
This portal gathers an annotated collection of recent research on the ways in which social media and new technologies may be leveraged in the fight against violent extremism