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This paper investigates the possibility of creating a machine learning toolthat automatically determines the state of mind and emotion of an individualthrough a questionnaire, without the aid of a human expert. The state of mindand emotion is defined in this work as pertaining to preference, feelings, oropinion that is not based on logic or reason. It is the case when a persongives out an answer to start by saying, "I feel...". The tool is designed tomimic the expertise of a psychologist and is built without any formal knowledgeof psychology. The idea is to build the expertise by purely computationalmethods through thousands of questions collected from users. It is aimedtowards possibly diagnosing substance addiction, alcoholism, sexual attraction,HIV status, degree of commitment, activity inclination, etc. First, the paperpresents the related literature and classifies them according to data gatheringmethods. Another classification is created according to preference, emotion,grouping, and rules to achieve a deeper interpretation and better understandingof the state of mind and emotion. Second, the proposed tool is developed usingan online addiction questionnaire with 10 questions and 292 respondents. Inaddition, an initial investigation on the dimension of addiction is presentedthrough the built machine learning model. Machine learning methods, namely,artificial neural network (ANN) and support vector machine (SVM), are used todetermine a true or false or degree of state of a respondent.

A Machine Learning Tool to Determine State of Mind and Emotion