Extraction of Multi-layered Social Networks from Activity Data

TL;DR

This paper introduces a novel method for extracting complex, multi-layered social networks from activity data in web systems, considering hierarchies and diverse relationships between users and objects.

Contribution

The paper presents a new approach for constructing multi-layered social networks from hierarchical activity data, enabling detailed analysis of user interactions.

Findings

Effective extraction of multi-layered social networks from activity data

Identification of new layers and relationships through flattening and preprocessing

Enhanced analysis of complex social structures in web-based systems

Abstract

The data gathered in all kind of web-based systems, which enable users to interact with each other, provides an opportunity to extract social networks that consist of people and relationships between them. The emerging structures are very complex due to the number and type of discovered connections. In webbased systems, the characteristic element of each interaction between users is that there is always an object that serves as a communication medium. This can be e.g. an email sent from one user to another or post at the forum authored by one user and commented by others. Based on these objects and activities that users perform towards them, different kinds of relationships can be identified and extracted. Additional challenge arises from the fact that hierarchies can exist between objects, e.g. a forum consists of one or more groups of topics, and each of them contains topics that finally include posts. In this paper, we propose a new method for creation of multi-layered social network based on the data about users activities towards different types of objects between which the hierarchy exists. Due to the flattening, preprocessing procedure new layers and new relationships in the multi-layered social network can be identified and analysed.