Identifying Social Media Influencers using Graph Based Analytics

AUTHORS

Pankti Joshi,Computer Science Department, Lakehead University, Ontario, Canada
Sabah Mohammed*,Computer Science Department, Lakehead University, Ontario, Canada

ABSTRACT

Social network analysis has been an essential topic with broad content sharing from social media. Defining the directed links in social media determine the flow of information and indicates the user’s influence. Due to the enormous data and unstructured nature of sharing information, there are several challenges caused while handling data. Graph Analytics proves to be an essential tool for addressing problems such as building networks from unstructured data, inferring information from the system, and analyzing the community structure of a network. The proposed approach aims to determine the influencers on Twitter data, based on the follower’s links as well as the retweet links. Several graph-based algorithms are implemented on the data collected to find the influencer as well as conversation communities in the network of twitter users.

 

KEYWORDS

Social media, Twitter, Influencers, Graph analytics, Graph database

REFERENCES

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CITATION

  • APA:
    Joshi,P.& Mohammed*,S.(2020). Identifying Social Media Influencers using Graph Based Analytics. International Journal of Advanced Research in Big Data Management System, 4(1), 35-44. 10.21742/IJARBMS.2020.4.1.04
  • Harvard:
    Joshi,P., Mohammed*,S.(2020). "Identifying Social Media Influencers using Graph Based Analytics". International Journal of Advanced Research in Big Data Management System, 4(1), pp.35-44. doi:10.21742/IJARBMS.2020.4.1.04
  • IEEE:
    [1] P.Joshi, S.Mohammed*, "Identifying Social Media Influencers using Graph Based Analytics". International Journal of Advanced Research in Big Data Management System, vol.4, no.1, pp.35-44, May. 2020
  • MLA:
    Joshi Pankti and Mohammed* Sabah. "Identifying Social Media Influencers using Graph Based Analytics". International Journal of Advanced Research in Big Data Management System, vol.4, no.1, May. 2020, pp.35-44, doi:10.21742/IJARBMS.2020.4.1.04

ISSUE INFO

  • Volume 4, No. 1, 2020
  • ISSN(p):2208-1674
  • ISSN(e):2208-1682
  • Published:May. 2020

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