Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review
The task of trying to quantify a person’s intelligence has been a goal of psychologists for over a century. The area of estimating IQ using stylometry has been a developing area of research and the effectiveness of using machine learning in stylometry analysis for the estimation of IQ has been demon...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2022-09-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2022.9020002 |
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| author | Glory O. Adebayo Roman V. Yampolskiy |
| author_facet | Glory O. Adebayo Roman V. Yampolskiy |
| author_sort | Glory O. Adebayo |
| collection | DOAJ |
| description | The task of trying to quantify a person’s intelligence has been a goal of psychologists for over a century. The area of estimating IQ using stylometry has been a developing area of research and the effectiveness of using machine learning in stylometry analysis for the estimation of IQ has been demonstrated in literature whose conclusions suggest that using a large dataset could improve the quality of estimation. The unavailability of large datasets in this area of research has led to very few publications in IQ estimation from written text. In this paper, we review studies that have been done in IQ estimation and also that have been done in author profiling using stylometry and we conclude that based on the success of IQ estimation and author profiling with stylometry, a study on IQ estimation from written text using stylometry will yield good results if the right dataset is used. |
| format | Article |
| id | doaj-art-2a276f4f3c084d10b12e41c09017979b |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2022-09-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-2a276f4f3c084d10b12e41c09017979b2025-02-02T06:50:33ZengTsinghua University PressBig Data Mining and Analytics2096-06542022-09-015316319110.26599/BDMA.2022.9020002Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A ReviewGlory O. Adebayo0Roman V. Yampolskiy1Department of Computer Science and Engineering, University of Louisville, Louisville, KY 40208, USADepartment of Computer Science and Engineering, University of Louisville, Louisville, KY 40208, USAThe task of trying to quantify a person’s intelligence has been a goal of psychologists for over a century. The area of estimating IQ using stylometry has been a developing area of research and the effectiveness of using machine learning in stylometry analysis for the estimation of IQ has been demonstrated in literature whose conclusions suggest that using a large dataset could improve the quality of estimation. The unavailability of large datasets in this area of research has led to very few publications in IQ estimation from written text. In this paper, we review studies that have been done in IQ estimation and also that have been done in author profiling using stylometry and we conclude that based on the success of IQ estimation and author profiling with stylometry, a study on IQ estimation from written text using stylometry will yield good results if the right dataset is used.https://www.sciopen.com/article/10.26599/BDMA.2022.9020002stylometryiq estimationauthorship attributionintelligenceiqauthor profilingmachine learning |
| spellingShingle | Glory O. Adebayo Roman V. Yampolskiy Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review Big Data Mining and Analytics stylometry iq estimation authorship attribution intelligence iq author profiling machine learning |
| title | Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review |
| title_full | Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review |
| title_fullStr | Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review |
| title_full_unstemmed | Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review |
| title_short | Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review |
| title_sort | estimating intelligence quotient using stylometry and machine learning techniques a review |
| topic | stylometry iq estimation authorship attribution intelligence iq author profiling machine learning |
| url | https://www.sciopen.com/article/10.26599/BDMA.2022.9020002 |
| work_keys_str_mv | AT gloryoadebayo estimatingintelligencequotientusingstylometryandmachinelearningtechniquesareview AT romanvyampolskiy estimatingintelligencequotientusingstylometryandmachinelearningtechniquesareview |