Emerging Trends in Personality Identification Using Online Social Networks—A Literature Survey

Abstract

Personality is a combination of all the attributes—behavioral, temperamental, emotional, and mental—that characterizes a unique individual. Ability to identify personalities of people has always been of great interest to the researchers due to its importance. It continues to find highly useful applications in many domains. Owing to the increasing popularity of online social networks, researchers have started looking into the possibility of predicting a user's personality from his online social networking profile, which serves as a rich source of textual as well as non-textual content published by users. In the process of creating social networking profiles, users reveal a lot about themselves both in what they share and how they say it. Studies suggest that the online social networking websites are, in fact, a relevant and valid means of communicating personality. In this article, we review these various studies reported in literature toward identification of personality using online social networks. To the best of our knowledge, this is the first reported survey of its kind at the time of submission. We hope that our contribution, especially in summarizing the previous findings and in identifying the directions for future research in this area, would encourage researchers to do more work in this budding area.

A large-scale, in-depth analysis of developers’ personalities in the Apache ecosystem

“…Psychologists have been able to identify correlations between specific linguistic markers and personality traits [43]. To date, there has been limited but growing amount of work on the automatic detection of personality traits from conversation transcripts and written text [44]. Thanks to the advancements in artificial intelligence (AI) and the widespread diffusion of social media contents, researchers have explored methods for the automatic recognition of various types of pragmatic variation in text and conversations, both short-lived, such as emotion, sentiment, and opinions [45][46][47], and more long-term, such as personality [48,49].…”

Personality Prediction from Social Networks text using Machine Learning

“…Studies can be carried out in the social network on other (word-based) content of a user's profile. The standard personality lists of questions can also serve as a valuable understanding of deep things by creating new features that may be removed or removed from the online social networking profile of the user [22].…”

A fusion fuzzy model for detecting phony accounts in social networks

“…A portion of account attributes utilized as a part of most papers are: numerical information [2,22], formal person, place or thing [22], names [17], self details and catchphrase. Diverse inquiries utilize distinctive strategies to decide the significance of the words, for example, word recurrence [9] and term frequency.…”

“…Agreement look is additionally used to remove RTC. In the work, Koushal et al [9] proposed a personality identification on decent variety half and half model for User phony account which incorporates few models: one is Maximal Marginal Importance model assorted varietyand the personal identification decent variety method and multihop profiling strategy. The MMI model strategy, RTC may arranged with double tree as indicated by the weights of decent variety, the multihop profile utilized in choosing RTC which incorporated into fake account removal technique.…”

“…Likewise, Viejo analyzes the searches of attributes of phony account afterward prepares includes in fuzz and fluffy. Koushal et al [9] proposed another RTC closeness measure and RTC based extractive system for detection of phony account. This technique depends on bunching and extraction of RTC.…”