Prediction of Selected Personality Traits Based on Text Messages from Instant Messenger

Woda, Marek; Batogowski, Jakub

doi:10.1007/978-3-030-48256-5_66

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…The survey consists of 50 pair-wise questions, following a widely used method referred to in [10,11,12,14,15], which facilitates the quantification of errors in respondents' answers. This is essential for the precise measurement of personality characteristics and reduces the tendency to under-or overestimate oneself.…”

Section: Course Of the Studymentioning

confidence: 99%

Authorial approach to the detection of selected psychological traits based on handwritten texts

Woda,

Oliwa

2024

International Journal of Electronics and Telecommunications

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The study sought to use computer techniques to detect selected psychological traits based on the nature of the writing and to evaluate the effectiveness of the resulting software. Digital image processing and deep neural networks were used. The work is complex and multidimensional in nature, and the authors wanted to demonstrate the feasibility of such a topic using image processing techniques and neural networks and machine learning. The main studies that allowed the attribution of psychological traits were based on two models known from the literature, KAMR and DA. The evaluation algorithms that were implemented allowed the evaluation of the subjects and the assignment of psychological traits to them. The DA model turned out to be more effective than the KAMR model.

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Section: Course Of the Studymentioning

confidence: 99%

Authorial approach to the detection of selected psychological traits based on handwritten texts

Woda,

Oliwa

2024

International Journal of Electronics and Telecommunications

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“…The test found that Belbin's roles can be identified based on personality traits. These personality traits can be extracted from communication platforms and educational environments such as Canvas or Discord [7].…”

Section: Introductionmentioning

confidence: 99%

Application of NLP on student’s Discord messages for automatic Belbin role identification

Dichev

Bukhsh

Fleitas

2022

2022 International Conference on Frontiers of Information Technology (FIT)

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Social media has found its way into education and, together with team formation, has started to play a significant role in students' university progress. Previous research has tried to generally analyze and give predictions about the influence of social media on students' learning curve but was not concentrated on understanding students' behavior within teams and directly linking it to Belbin roles, which is crucial for forming teams. In this paper, we are working with real-life data extracted from official university channels will allow us to propose a methodology and a pilot Belbin role automation tool to look further into the specifics of the problem. In addition, linking this to team roles and behavior concerns within the project teams will open the horizon for further research on how the performance of students within the teams is affected. We propose to create a primary tool and framework for validating Belbin roles through real-life social network data. Results show that it is possible to identify Belbin's roles using natural language processing. The future work direction is to refine the words associated with every personality trait.

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Analysis of Handwritten Texts to Detect Selected Psychological Characteristics of a Person

Woda,

Oliwa

2023

Lecture Notes in Networks and Systems

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Prediction of Selected Personality Traits Based on Text Messages from Instant Messenger

Cited by 3 publications

References 11 publications

Authorial approach to the detection of selected psychological traits based on handwritten texts

Authorial approach to the detection of selected psychological traits based on handwritten texts

Application of NLP on student’s Discord messages for automatic Belbin role identification

Analysis of Handwritten Texts to Detect Selected Psychological Characteristics of a Person

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