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Statistical Analysis of Classification Algorithms for Predicting Socioeconomics Status of Twitter Users
[thesis]
The purpose of this study is to compare a series of well-known statistical machine learning techniques that classify online social network (OSN) Twitter users based on their socioeconomic status (upper/middle/lower). These approaches are of difference owing to their assumptions, strengths, and weaknesses. In the experiments, five (5) classification algorithms are employed for the classification task. Logistic Regression, Support Vector Machine (SVM), Naïve Bayes (NB), k-Nearest Neighbors, and
doi:10.22215/etd/2017-11995
fatcat:bxh3473duvgl3py2e3b5w56h4u