A General Personality Prediction Framework Based on Facebook Profiles

Zhong, Xiaofeng; Guo, Shize; Gao, Liang; Hong, Soondo; Xue, Di

doi:10.1145/3195106.3195124

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…Gavrilescu and Vizireanu [3] proposed a neural network based model that determines the Big-5 personality traits of an individual by analysing offline handwriting. Zhong et al [4] proposed [BE] help others; works on general welfare Conformity [CO] follows rules, laws and structures Hedonism [HE] seeks pleasure and enjoyment Power [PO] dominates and controls others and resources Security [SE] seeks safety, security, and social stability Self-direction [SD] free and independent in thoughts and actions Stimulation [ST] seeks excitement and thrills Tradition [TR] accepts customs and ideas provided by religion Universalism [UN] prefers peace; works toward social welfare a personality prediction framework, consisting of outlier elimination, training dataset selection and personality prediction. Rammstedt et al [5] comprehensively investigated the associations between both fluid and crystallised intelligence with Big-5 personality domains as well as their facets.…”

Section: The Paradox Of Homophilymentioning

confidence: 99%

“…So did Gavrilescu and Vizireanu [3] propose a neural network based model that determines the Big Five personality traits of an individual by analysing offline handwriting. Zhong et al [4] utilised a personality prediction framework consisting of outlier elimination, training dataset selection and personality prediction. Rammstedt et al [5] comprehensively investigated the associations between both fluid and crystallised intelligence with Big Five personality domains as well as their facets.…”

Section: User Demographic and Propertiesmentioning

confidence: 99%

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Understanding the Psycho-Sociological Facets of Homophily in Social Network Communities

Solomon

Pykl

Das

et al. 2019

IEEE Comput. Intell. Mag.

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Community" in social networks is a nebulous concept. A community is generally assumed to be formed by people who possess similar attributes or characteristics, also known as "homophily". Although there has been a lot of research on community detection based on network topology, the semantic interpretation of communities is rarely studied. The present work aims to understand the behavioural similarity of users present in their personal neighbourhood communities formed by friends, relatives, or colleagues, and addresses two fundamental questions: (i) Are communities formed by users who possess similar behavioural traits? If so, does this apply to all those sub-networks, i.e., friends, relatives, and colleagues? (ii) Does adding behavioural node-specific attributes/features to the nodes in a network lead to better community detection? To better understand the psycho-sociological homophilic nature of personal networks, the personalities and values of Twitter users were analysed using the well-established "Big-5 personality model" and "Schwartz sociological behaviour model". Empirical results based on the psycho-sociological behaviour show that friends networks exhibit homophily, whereas relatives and colleagues networks do not exhibit such homophilic behaviour. It can also be observed that neurotic people tend to behave heterogeneously with people of various personality traits. In addition, it is shown that such empirical evidence can be used as features for the tasks of community detection and link prediction.

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Section: The Paradox Of Homophilymentioning

confidence: 99%

Section: User Demographic and Propertiesmentioning

confidence: 99%

Understanding the Psycho-Sociological Facets of Homophily in Social Network Communities

Solomon

Pykl

Das

et al. 2019

IEEE Comput. Intell. Mag.

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“…Some related studies have proposed methods to perform personality prediction. Among them, To determine the distance between samples, detect outliers, and apply the maximum interval criteria and support vector machine method for personality prediction, Zhong et al recommended using Mahalanobis distance and Z-value [2]; By building an end-to-end video analytics network based on 3D-ConvNet, Xu et al improved the accuracy of personality prediction by addressing the issue of network overfitting [3]; Wang et al used Attention Recurrent Neural Networks (AttRNNs) to solve the problem of neglecting the temporal features of digital footprints by commonly used classification models, and proposed an effective method for predicting personality features [4]. Si et al introduced a Bert-LSTM model to address the challenge of limited text utilization in textual sentiment analysis tasks.…”

Section: Introductionmentioning

confidence: 99%

A review-based approach to user profiling

2024

ACE

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With the popularity of social media, sentiment analysis and text categorisation by analysing the information people post online has become an effective method to study personality prediction. This paper focuses on how to use a personality prediction model based on Bidirectional LSTM for personality prediction. Accurate personality prediction results can provide personalised recommendation services for individuals, which has certain commercial value. In this paper, the dataset of Kaggle is first preprocessed, and then the Bidirectional LSTM model is constructed and the hyperparameters are set.The processed data are then put into the model for training and testing. Finally, the above steps are repeated using other different machine learning models. After comparison experiments with other common machine learning models, it was found that the Bidirectional LSTM model showed significant advantages in the personality prediction task, and its accuracy reached 93.5%, which was significantly higher than the traditional machine learning model.

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A Study of Data Mining Methods for Prediction of Personality Traits

Desai

Patel

2020

2020 International Conference on Smart Electronics and Communication (ICOSEC)

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A General Personality Prediction Framework Based on Facebook Profiles

Cited by 4 publications

References 24 publications

Understanding the Psycho-Sociological Facets of Homophily in Social Network Communities

Understanding the Psycho-Sociological Facets of Homophily in Social Network Communities

A review-based approach to user profiling

A Study of Data Mining Methods for Prediction of Personality Traits

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