Fake News Classification in Twitter Data Using Innovative K Nearest Neighbor Comparing Logistics Regression
Ajay Kumar V, R Surendran, N Madhusundar. · 2023
Improve the accuracy of identifying fake news on Twitter by employing the Advanced K Nearest Neighbor Algorithm then evaluating the results against those obtained through Logistic Regression Algorithm. Materials and Methods: The research is divided into two groups, each with a sample size of 42 individuals. The first group, comprising 21 participants, will apply the Advanced K Nearest Neighbor Algorithm, while the second group, also consisting of 21 participants, will use the Logistic Regression technique. The study has been designed with G power 80% parameters of α=0.05 and beta=0.2. Result: Innovative K nearest neighbor Algorithm 81.55 % identifies objects and increases the measured accuracy over Logistic Regression 79.0 % with implication value of 0.001 (p < 0.05). Conclusion: In terms of accuracy, the Innovative K Nearest Neighbor Algorithm outperforms Logistic Regression Algorithm.