  Humans are social by nature. Throughout history, people have formed
communities and built relationships. Most relationships with coworkers,
friends, and family are developed during face-to-face interactions. These
relationships are established through explicit means of communications such as
words and implicit such as intonation, body language, etc. By analyzing human
interactions we can derive information about the relationships and influence
among conversation participants. However, with the development of the Internet,
people started to communicate through text in online social networks.
Interestingly, they brought their communicational habits to the Internet. Many
social network users form relationships with each other and establish
communities with leaders and followers. Recognizing these hierarchical
relationships is an important task because it will help to understand social
networks and predict future trends, improve recommendations, better target
advertisement, and improve national security by identifying leaders of
anonymous terror groups. In this work, I provide an overview of current
research in this area and present the state-of-the-art approaches to deal with
the problem of identifying hierarchical relationships in social networks.

Computation and Language;Artificial Intelligence;Social and Information Networks