Personality Traits Recognition on Social Network - Facebook

2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS)

Personality is an important parameter because it distinguishes different people from each other.The prediction of personality is a field of constant research.Prediction of personality by means of social data the media is a promising approach because it does not require this method any user-filled questionnaires reducing time and increasing credibility. The utilisation of social mediaDay by day increased. Extensive amounts of textual data andthe pictures keep bursting into the web every day.Current work focuses on machine learning Naive Bayes and Decision tree over Facebook standard dataset.

Predicting Personality with a much more accuracy that can be very useful for the betterment of the society. And many of the researchers were conducted a use of the given data for the purpose of organizational development, social marketing network, individually recognized recommendations and health care systematic. And with an introduction the popularity of the social media networking websites or online platforms like Twitter, Facebook and LinkedIn researchers were conducted based on the given data from public are available through the online social networking platforms and social behaviors aspects that could help to the friends and followers for the much prediction of personality. In the paper we proposed a system that mainly aims to automate the personality prediction assessment process by training a model using Myers Briggs Type Indicator (MBTI) personality prediction analysis. Online social media platforms networks provide more and more opportunity from knowledge perspective discovery and the data from public with respect to their view. The Structured information of the social media networking content can be provided with the knowledge to predict the main and important of the personality traits. People nowadays share some of their thoughts, information, feelings more specifically their personality traits, on social media platforms more often they are the sources of data generation. Many researchers faced problems and many challenges and still they facing and working towards on and in the future, there is plenty of opportunity for many research to predict it with the better accuracy and good results.

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.

—Personality is a fundamental basis of human behavior. Personality affects the interaction and preferences of an individual. People are required to take a personality test to find out their personality. Social media is a place where users express themselves to the world. Posts made by users of social media can be analyzed to obtain their personal information. This experiment uses text classification to predict personality based on text written by Twitter users. The languages used are English and Indonesian. Classification methods implemented are Naive Bayes, K-Nearest Neighbors and Support Vector Machine. Testing results showed Naive Bayes slightly outperformed the other methods.

International Journal of Electrical and Computer Engineering (IJECE), 2022

The popularity of social media has drawn the attention of researchers who have conducted cross-disciplinary studies examining the relationship between personality traits and behavior on social media. Most current work focuses on personality prediction analysis of English texts, but Indonesian has received scant attention. Therefore, this research aims to predict user's personalities based on Indonesian text from social media using machine learning techniques. This paper evaluates several machine learning techniques, including naive Bayes (NB), K-nearest neighbors (KNN), and support vector machine (SVM), based on semantic features including emotion, sentiment, and publicly available Twitter profile. We predict the personality based on the Big Five personality model, the most appropriate model for predicting user personality in social media. We examine the relationships between the semantic features and the Big Five personality dimensions. The experimental results indicate that the Big Five personality exhibit distinct emotional, sentimental, and social characteristics and that SVM outperformed NB and KNN for Indonesian. In addition, we observe several terms in Indonesian that specifically refer to each personality type, each of which has distinct emotional, sentimental, and social features.

SAGE Open

Everyday, social media usage particularly Facebook usage are growing exponentially. Simply, inspecting Facebook usage provides meaningful information concerning users’ daily interactions and hence about their personality traits. Numerous studies have been done to harness such streams of Facebook data to obtain accurate prediction of human behavior, social interactions, and personality. The aim of this study is to build a neural network–based predictive model that uses Facebook user’s data and activity to predict the Big 5 personalities. This study combines the inference features highlighted in three different relevant studies which are; number of likes, events, groups, tags, updates, network size, relationship status, age, and gender. The study was conducted on 7,438 unique Facebook participants obtained from the myPersonality database. The findings of this study showed how much a person’s personality can be predicted only by analyzing their Facebook activity. The proposed artificia...

IRJET, 2022

Personality is an critical aspect that influences someone's opinions, like-dislike, thoughts, and the way someone behaves in exceptional situations. Nowadays social media is a platform wherein human beings explicit their view, how they feel, what they're doing. Every 2nd on average, round 6000 tweets are generated. This records may be analyzed nicely to are expecting the character of the consumer. In this project, we'll display you a way to use gadget getting to know to examine someone's character primarily based totally on their real-time Twitter feed. Specifically, we'll first use the Twitter API you purchased our enter records earlier than going for walks a naive Bayes classifier to educate and check our version, so as to then be capable of categorize new Twitter profiles stay right into a Myers-Briggs Type Indicator (MBTI). We're already acquainted with the famous metric, which makes use of a four-letter end result (consisting of INFJ or ENFP) to summarize exceptional character traits in phrases of ways people understand the sector and make decisions. Normally, that is derived via questionnaires and psychometric checks administered to every person, however right here we'll robotically get a end result at the pressing of a button. Models anticipated every character trait with the accuracy 76.231%.

User Modeling and User-Adapted Interaction, 2016

A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different online environments? and What is the decay in accuracy when porting models trained in one social media environment to another?

Language has a well-established link with personality, your social media language revels about you. Facebook is one of the most popular social networks where users express their views and feelings through posts and statuses. In this paper we describe the method of assessing personality using Facebook Posts. Personality can be judge through various methods of Psychology we use the Big Five Model. We also find correlation between these five traits to figure out the relation between them. We examine the difficulty of collecting profile data from Facebook so we develop an application Predict Me to fetch the data. Our results highlight how a person's personality can be judge through its Facebook profile and how much these traits are correlated with each other.

International Journal of Engineering Research and, 2020

Individual Personality can be predicted by using Online Social Networks. The Predicted personality finds its application in various fields. This paper proposes a system to predict the personality scores of the student without having to go through any personality analysis or taking any personality test. The results obtained clearly indicate that machine learning models can be effectively used for student's personality prediction from Big-5 Traits. The BIG-FIVE Model Big-5 model popularly known as OCEAN model [6] [2] consists of Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism. Openness consists of six concepts, or a scale, counting consistent creative ability, tasteful affectability, thoughtfulness to inward sentiments, inclinations for assortment, and mental interest. Conscientiousness deduces on ache for to do a task well, and to expect responsibilities to others genuinely. Extroversion demonstrates how active and social a person is. Agreeableness is personality trademark showcased in person's social behaviour that are seen as mindful, pleasing, warm and valiant. People having high score in neuroticism encounter sentiments such as uneasiness, stress, fear, outrage, dissatisfaction, envy, blame, discourage temperament and depression. The Big-5 model is one of the most studied models and many researches have proved that irrespective of any language, test or the method of analysis the validity of the model does not change [13] [14] [15] [16]. So Big5 is