This research proposes a feature extraction algorithm based on demographic and personality attributes on social media. The attributes including gender, age group, political affiliation, religion, and personality types are analyzed. Two feature sets are extracted for each user, including the comment text and community activity. Naïve Bayes and logistic regression classifier are performed to evaluate the attribute prediction. A dataset of comments from the Reddit website is obtained as a case study. Experimental results measured in term of F1 score are 88% in predicting user’s political affiliation, 85% for gender, 57% for religion, 46% for personality type, and 42% for the age group. We found that the feature set obtained from user activity provides better performance in the user recognition task.
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