Multigraph Anomaly Detection in Social Networks

By Manjunatha H C

The point at which a PC network links individuals or associations, it becomes a social platform. Similar to the computer network where set of interacted devices connected by set of wires and network buses, social networks consist of people (or institutes or other social groups) joined by a set of societal relations, such as colleagues, friends and exchange of information. From the past few years, Online Social Networks (OSN) observed exponential rise in the trend of people who joined these networking platforms. Being a resilient mode of communication, these platforms have become a trendy tool to give opinion on events occurring around the globe, increase knowledge discovery, and assist in social communication.

In addition, OSNs are highly influential platform not only limited to connection among family and friends, but also provide access to get connected with professional groups. Moreover, they can be utilised for the purpose of publicizing and promoting for improving business repute in the market. Individuals join online social networks, build their personal profiles, and get connected to other people of the network having same interest for the purpose of keep updated and in touch with each other.

In past few years, especially during pandemic Covid-19 the drastic increase in digitalization of many platforms, businesses and online social platforms has been observed which highlights that these social media platforms OSN are becoming essential part in Social Network Analysis (SNA). This incorporates in depth investigation into the revealing of glitches in social sites, and develops the methods. In these social networks anomalies results as an outcome of individual user, or groups of users, by doing abrupt changes in the way of communication or communicating in a fashion that significantly varies from other colleagues. The effect of these irregular behaviours can be detected in the subsequent network configuration.

• Format: Paperback
• Language: English
• ISBN: 1835801005
• ISBN13: 9781835801000
• Release Date: February 2024
• Publisher: Mohammed Abdul Sattar
• Length: 124 Pages
• Weight: 0.67 lbs.
• Dimensions: 11.0" x 0.3" x 8.5"