Personality Prediction Through Handwriting Analysis Using Convolutional Neural Networks

Chaubey, Gyanendra; Arjaria, Siddhartha Kumar

doi:10.1007/978-981-16-3802-2_5

Cited by 13 publications

(13 citation statements)

References 20 publications

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“…In comparison to Mekhaznia et al [7] proposed solution had 8% higher accuracy. In comparison to Chaubey and Arjaria [29] proposed solution has 43% higher accuracy. The combined use of document level and character level features along with error loss minimization based loop back control in the proposed solution has increased the accuracy.…”

Section: Resultsmentioning

confidence: 82%

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A self adaptive cognitive deep learning framework for classifying graphology features to Big five personality traits

2022

IJATEE

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Graphology is a technique for study and analysis of individual personality from his/her handwriting style. Most of the existing graphology-based solutions for personality detection recognize nonstandard application dependent personalities. Even the very few big five personality recognition approaches have limited accuracy and lacks adaptivity to new handwriting styles. Towards these problems, a novel self-adaptive cognitive learning framework based on deep learning convolutional neural network (CNN) features is proposed to classify the handwritten document to big five personality traits. This framework correlates the various document level and character level graphology features to big five personality traits to recognize features with strong correlation to various big five personality traits and uses these features to classify the personality. To enhance the deep learning feature learning ability an enhanced convolution kernel is proposed for the CNN. Through testing with various handwritten documents, the proposed solution is found to provide 2.18% higher accuracy and 5% lower false positives compared to existing works on big five personality classification.

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Section: Resultsmentioning

confidence: 82%

“…(2021) [7], Chaubey and Arjaria (2022) [29] were used. The accuracy results for different personality types are given in Table 7.…”

Section: Resultsmentioning

confidence: 99%

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A self adaptive cognitive deep learning framework for classifying graphology features to Big five personality traits

2022

IJATEE

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“…Talent acquisition and talent management consider psychometric profiling an important step as many business leaders have admitted that mindset is more important than skill-set in a dependable candidate. 2 The most recent domains that researchers have started looking into to understand the personality of person are facial cues, 3,4 speech, 5 handwriting 6 and oddball questions. 7 Some new fields where the use of personality profiling is proposed is cyber threat intelligence, where Reference 8 found out that the personality of each hacker is correlated with the pattern of their hacking and their expertise level.…”

Section: Introductionmentioning

confidence: 99%

“…The most recent domains that researchers have started looking into to understand the personality of person are facial cues, 3,4 speech, 5 handwriting 6 and oddball questions 7 . Some new fields where the use of personality profiling is proposed is cyber threat intelligence, where Reference 8 found out that the personality of each hacker is correlated with the pattern of their hacking and their expertise level.…”

Section: Introductionmentioning

confidence: 99%

Psychometric profiling of individuals using Twitter profiles: A psychological Natural Language Processing based approach

Rathi

Verma

Jain³

et al. 2022

Concurrency and Computation

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The recent pandemic saw the operations of many businesses shifting to virtual mode. Tasks like psychometric analysis of individuals, for various applications, are conducted online. In this article, we introduce a novel system to analyze the semantics of an individual's tweets from their Twitter profile using LIWC and SALLEE scores. These scores can be used to evaluate less fortunate, thin‐filed candidates using their Twitter profiles. With increased access to phones and the internet, many organizations are focusing on making credit systems available to the masses by introducing psychometric analysis. This article proposes a dynamic model for evaluating the personality of a Twitter user using the textual content shared on their page. The model will allow stakeholders to ascertain the personality of user according to any personality model. To analyze if this is viable and flexible approach to model any kind of personality model, we take MBTI personality dataset and train classifier to predict personality types. Then these results are correlated with a linguistic score to find correlation between the two. We found that proposed approach, outperformed the other relevant works also some aspects of these linguistic scores show a heavy correlation with certain personality types.

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Review of Handwriting Analysis for Predicting Personality Traits

Tang

Suen

2022

Lecture Notes in Computer Science

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Personality Prediction Through Handwriting Analysis Using Convolutional Neural Networks

Cited by 13 publications

References 20 publications

A self adaptive cognitive deep learning framework for classifying graphology features to Big five personality traits

A self adaptive cognitive deep learning framework for classifying graphology features to Big five personality traits

Psychometric profiling of individuals using Twitter profiles: A psychological Natural Language Processing based approach

Review of Handwriting Analysis for Predicting Personality Traits

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