Abstract
Many youngsters go through a stressful adolescent phase of their life which may lead to depression. It is generally associated with emotional and socioeconomic pressure they are subjected to. This may lead to aggressive and risky behavior, substance abuse, and self-harm. Young people spend considerable amount of time on social media to stay connected with friends, teachers, family, and other peer group. Hence, it can be used as an effective tool to disseminate information to those affected young people at a faster pace. The study is centered around identifying emotional quotient of young people through their Facebook posts. We collected Facebook status updates which are written in both Hindi and English languages, studied them and classified them by using six different classifiers (support vector machine, multinomial Naïve Bayes, PART, IBk, Naïve Bayes, and J48) to identify the emotional polarity. Multinomial Naïve Bayes generated the highest accuracy of 95% when tested with unigram and bigram models. We conclude that youngsters who are going through some psychological pressure tend to exhibit some peculiar characteristic features through their posts than the normal people.
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Sinha, S., Saxena, K., Joshi, N. (2019). Sentiment Prediction of Facebook Status Updates of Youngsters. In: Shukla, R.K., Agrawal, J., Sharma, S., Singh Tomer, G. (eds) Data, Engineering and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-13-6347-4_9
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DOI: https://doi.org/10.1007/978-981-13-6347-4_9
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