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@article{150517, author = {Kalpesh Rajendra Dhomane and Mamata Jankiram Kapure and Ashish Annasaheb Naikwadi and Sayali Dilip Handore and Prof.Hardik Gosavi}, title = {Personality prediction using Data of Facebook}, journal = {International Journal of Innovative Research in Technology}, year = {}, volume = {7}, number = {7}, pages = {108-110}, issn = {2349-6002}, url = {https://ijirt.org/article?manuscript=150517}, abstract = {We examine to which degree behavioural measures can be used to predict personality. Personality is one factor that dictates people’s propensity to trust and their relationships with others. One’s personality is widely accepted as an indicator of job performance, job satisfaction and tenure intention. The ability to measure an applicant’s personality in the selection process helps recruiters, hiring managers and the applicant make better hiring decisions. Personality can be predicted relatively accurately by analysing social media profiles. We demonstrated this using public data from Facebook profiles. As social situations are crucial in the formation of one’s personality, one’s social behaviour could be a strong indicator of her personality. Given most users of social media sites typically have a large number of friends and followers, considering only these aspects may not provide an accurate picture of personality. To overcome this problem, we develop a set of measures based on one’s behaviour towards her friends and followers. We introduce a number of measures that are based on the intensity and number of social interactions one has with friends along a number of dimensions such as reciprocity and priority. We analyse these features along with a set of features based on the textual analysis of the messages sent by the users. We show that behavioural features are very useful in determining personality and perform as well as textual features }, keywords = {Personality traits, influence, trust and relationship with others, Social Situations, Accurate Personality Prediction. }, month = {}, }
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