Predicting the Primary Dominant Personality Trait of Perceived Leaders by Mapping Linguistic Cues from Social Media Data onto the Big Five Model
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in today’s world of a virtually interconnected society, the number of social media users (facebook, twitter, instagram, etc.) is ever-increasing. social media has become very popular and one of the main channels of communication with users share different types of information—updates, posts, pictures, etc. twitter—a microblogging site—has become increasingly popular platform over the last few years with 330 million monthly active users, who on average generate 6000 tweets every second. the continued and growing use of social media has resulted in the generation of very large volumes of social media data, which can be used for research purposes. one potential application is automatic personality prediction—which aims to analyze social data and predict the users’ personality traits. this is possible because people inadvertently leave behind linguistic cues to personality in their social data. these cues, if properly mined, provide a short cut to personality detection of users. using digital records to predict personality offers an alternative solution to overcome the drawbacks of manual methods, which while being accurate are time-consuming and expensive. in this work, an attempt is made to predict the primary dominant trait of leaders using social media data.
KeywordsPersonality Leadership Sentiment analysis Big five Personality trait prediction Machine learning
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