List of Articles personality

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  1 - An Intelligent Model for Multidimensional Personality Recognition of Users using Deep Learning Methods
  Hossein Sadr fatemeh mohades deilami morteza tarkhan
  20.1001.1.27170414.1400.13.47.6.2
  Due to the significant growth of textual information and data generated by humans on social networks, there is a need for systems that can automatically analyze the data and extract valuable information from them. One of the most important textual data is people's opini More

  Due to the significant growth of textual information and data generated by humans on social networks, there is a need for systems that can automatically analyze the data and extract valuable information from them. One of the most important textual data is people's opinions about a particular topic that are expressed in the form of text. Text published by users on social networks can represent their personality. Although machine learning based methods can be considered as a good choice for analyzing these data, there is also a remarkable need for deep learning based methods to overcome the complexity and dispersion of content and syntax of textual data during the training process. In this regard, the purpose of this paper is to employ deep learning based methods for personality recognition. Accordingly, the convolutional neural network is combined with the Adaboost algorithm to consider the possibility of using the contribution of various filter lengths and gasp their potential in the final classification via combining various classifiers with respective filter sizes using AdaBoost. The proposed model was conducted on Essays and YouTube datasets. Based on the empirical results, the proposed model presented superior performance compared to other existing models on both datasets. Manuscript profile
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  2 - Investigation the role of personality and individual differences on password security breaches: An Empirical Study
  زهرا کریمی manije kaveh rezvan salehi milad moltaji
  20.1001.1.27170411.1400.13.49.9.4
  The individual differences of Information Technology users influence on the selection and maintenance of passwords. To fill this gap, this paper, studies the relationships between gender, personality, education level and field of study in one direction and password secu More

  The individual differences of Information Technology users influence on the selection and maintenance of passwords. To fill this gap, this paper, studies the relationships between gender, personality, education level and field of study in one direction and password security in another direction. The method was descriptive and correlational. A sample selected by Convenience sampling, answered the NEO Five-Factor Model, biographical and password security behavior questionnaires. The data of 529 accepted questionnaires were analyzed using Pearson, T-Test, anova and regression the results showed that male users select stronger passwords compared to female users. The users in mathematical science, computer science, and also accounting, breached password security more often in comparison with users in other majors. Neuroticism has positive relationship, Openness-to-Experience and Agreeableness has negative relationships and Conscientiousness has a dual relationship with password security breach. These findings contribute to cybersecurity, especially in Iran, by considering individual differences in security behaviors and perceptions. Manuscript profile
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  3 - A Recommender System Based on the Analysis of Personality Traits in Telegram Social Network
  Mohammad Javad shayegan mohadeseh valizadeh
  <p style="text-align: left;"><span style="font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Nazanin; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: FA;">Analysis of perso More

  <p style="text-align: left;"><span style="font-size: 12.0pt; font-family: 'Times New Roman',serif; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: Nazanin; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: FA;">Analysis of personality traits of individuals has always been one of the interesting research topics. In addition, achieving personality traits based on data obtained from individuals' behavior is a challenging issue. Most people spend most of their time on social media and may engage in behaviors that represent a character in cyberspace. There are many social networks today, one of which is the Telegram social network. Telegram also has a large audience in Iran and people use it to communicate, interact with others, educate, introduce products and so on. This research seeks to find out how a recommendation system can be built based on the personality traits of individuals. For this purpose, the personality of the users of a telegram group is identified using three algorithms, Cosine Similarity, MLP and Bayes, and finally, with the help of a recommending system, telegram channels tailored to each individual's personality are suggested to him. The research results show that this recommending system has attracted 65.42% of users' satisfaction.</span></p> Manuscript profile