Graphology

About: Graphology is a research topic. Over the lifetime, 214 publications have been published within this topic receiving 2492 citations.

Handwriting Analysis for Detection of Personality Traits using Machine Learning Approach

Abstract: Among all the unique characteristics of a human being, handwriting carries the richest information to gain the insights into the physical, mental and emotional state of the writer. Graphology is the art of studying and analysing handwriting, a scientific method used to determine a person‟s personality by evaluating various features from the handwriting. The prime features of handwriting such as the page margins, the slant of the alphabets, the baseline etc. can tell a lot about the individual. To make this method more efficient and reliable, introduction of machines to perform the feature extraction and mapping to various personality traits can be done. This compliments the graphologists, and also increases the speed of analysing handwritten samples. Various approaches can be used for this type of computer aided graphology. In this paper, a novel approach of machine learning technique to implement the automated handwriting analysis tool is discussed.

Illusory correlations in graphological inference.

Abstract: The authors investigate the illusory correlation phenomenon as a possible contributor to the persistence of graphology's use to predict personality. Participants unfamiliar with graphology inspected handwriting samples paired with fabricated personality profiles. In Experiment 1, handwriting samples and personality profiles were randomly paired. In Experiment 2, discernible correlations near unity were set between targeted handwriting-feature-personality-trait pairs in a congruent or incongruent direction with graphologists' claims. In both experiments, participants' judgments of the correlation between designated handwriting-feature-personaiity-tralt pairs agreed with graphologists' claims, even after controlling for their actual statistical association. Semantic association between words used to describe handwriting features and personality traits was the source of biases in perceived correlation. Results may partially account for continued use of graphology despite overwhelming evidence against its predictive validity. "Beware of a man whose writing sways like a reed in the wind." Like Confucius, the graphologist makes inferences about personality by examining aspects of handwriting. In the past several decades, organizations around the world have begun to use the graphologist's assessment as a decision aid in personnel selection. The use of graphology in personnel selection is most prevalent in Europe, particularly France, where estimates for the percentage of organizations using the technique range from 38% (Shackleton & NeweR, 1994) to 93% (Brnchon-Schweitzer & Ferrieux, 1991). In the United States, estimates for the number of organizations using graphology rose from 500 in 1970 (Mickels, 1970) to 3,000 in 1977 (Hager, 1977), and more recent reports suggest that graphology is quietly gaining acceptance in corporate America (McCarthy, 1988). Although it is difficult to accurately assess how many organizations are using graphology, it does appear that hiring decisions regarding a large number of job applicants around the world are determined, at least in part, by inferences made on the basis of their handwriting. For the practice of graphology to persist, a perception among its users that the method bears some utility or predictive validity must exist. Indeed, many human-resource practitioners give positive testimony to the predictive power of graphology and continue to procure the services of graphologists (Hooper & Stanford, 1992; McCarthy, 1988). Although the idea of diagnosing personality from handwriting may bear some intuitive appeal, evidence for its validity is weak. Despite some early support from the scientific community (Allport & Vernon, 1933; Downey, 1923), the results of recent re

Inferring gender from handwriting in Urdu and English.

Abstract: Handwriting samples in both English and Urdu from 30 donors were judged for masculinity-femininity by 25 judges (both judges and donors were adult Pakistanis, bilingual and literate in both Urdu and English). Inferences about gender were made reliably and accurately in both Urdu and English. Levels of accuracy (about 68%) were similar to those reported in studies of handwriting in English. Judged gender of handwriting was significantly stable across the two languages studied. These effects are relevant for the study of gender roles and gender stereotyping in assessment.