Detecting influencers in social networks through machine learning techniques

Rishabh Makhija, Syed Ali, R. Jaya Krishna

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The online social networks have given access to a new way of communication in society. Social networking platforms like Facebook, Instagram and Twitter provide different ways to connect and communicate with people around the world, bringing together the ideas from different parts of the world. In every social network, there would be people who would be influential and can influence other people to their idea. Hence, finding an influential person is very important and helps us to spread information more accurately and to more people. In this paper, we worked with machine learning techniques to identify the most influential nodes in the network, studied different methods to determine the best suitable for the network and understood how information cascading techniques can be applied.

Original languageEnglish
Title of host publicationAdvanced Machine Learning Technologies and Applications - Proceedings of AMLTA 2020
EditorsAboul Ella Hassanien, Roheet Bhatnagar, Ashraf Darwish
PublisherSpringer Gabler
Pages255-266
Number of pages12
ISBN (Print)9789811533822
DOIs
Publication statusPublished - 2021
Event5th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2020 - Jaipur, India
Duration: 13-02-202015-02-2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1141
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference5th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2020
Country/TerritoryIndia
CityJaipur
Period13-02-2015-02-20

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • General Computer Science

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