A hybrid framework to predict influential users on social networks

Author(s):  
Khaled Almgren ◽  
Jeongkyu Lee
Author(s):  
Michael Trusov ◽  
Anand V. Bodapati ◽  
Randolph E. Bucklin

2010 ◽  
Vol 47 (4) ◽  
pp. 643-658 ◽  
Author(s):  
Michael Trusov ◽  
Anand V. Bodapati ◽  
Randolph E. Bucklin

Author(s):  
Johnnatan Messias ◽  
Lucas Schmidt ◽  
Ricardo Oliveira ◽  
Fabrício Benevenuto

Systems that classify influential users in social networks have been used frequently and are referenced in scientific papers and in the media as an ideal standard of evaluation of influence in the Twitter social network. We consider such systems of evaluation to be complex and subjective, and we therefore suspect that they are vulnerable and easy to manipulate. Based on this, we performed experiments and analysis of two systems for ranking influence: Klout and Twitalyzer. We created simple robots capable of interacting by means of Twitter accounts, and we measured how influent they were. Our results show that it is possible to become influential through simple strategies. This suggests that the systems do not have ideal means to measure and classify influence.


2019 ◽  
Vol 493 ◽  
pp. 217-231 ◽  
Author(s):  
Ahmad Zareie ◽  
Amir Sheikhahmadi ◽  
Mahdi Jalili

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