Predicting and Mitigating the Effect of Skewness on Credibility Assessment of Social Media Content Using Machine Learning: A Twitter Case Study

Author:

Basharat Shifaa,Afzal Saduf,Bamhdi Alwi M,Khurshid Shozab,Chachoo Manzoor

Publisher

IACSIT Press

Subject

Computational Theory and Mathematics,Computer Science Applications

Reference43 articles.

1. [1] Social media fact sheet. (2021). Pew Research Center. [Online]. Available: http://www.pewinternet.org/fact-sheet/social-media/

2. [2] Internet overtakes newspapers as a news outlet. (2008). Pew Research Center. [Online]. Available: http://pewresearch.org/pubs/1066/internet-overtakes-newspapers-as-newssource

3. [3] K. Thirunarayan, P. Anantharam, C. Henson, and A. Sheth, "Comparative trust management with applications: Bayesian approaches emphasis," Future Generation Computer Systems, vol. 31, pp. 182-199, 2014.

4. [4] S. Pogatchnik, "Student hoaxes world's media on Wikipedia," MSNBC Technology & Science, vol. 12, 2009.

5. [5] S. Laird. (2012). How social media is taking over the news industry. Mashable. [Online]. Available: https://mashable.com/archive/social-media-and-the-news

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