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Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage
Abstrakt
Purpose The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements. Design/methodology/approach An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks were calculated for each data sample. Then several machine learning methods were used to verify the stated research question. Findings The experiment showed that it is possible to recognise males and females on the basis of behavioural characteristics with an accuracy exceeding 70 per cent. The best results were obtained while using Bayesian networks. Research limitations/implications The first limitation of the study was the restricted contextual information, i.e. neither the type of web page browsed nor the user activity was taken into account. Another is the narrow scope of the respondent group. Future work should focus on gathering data from more users covering a wider age range and should consider the context. Practical implications Automatic gender recognition could be used in profiling a user to create personalised websites or as an additional feature in automatic identification for security reasons. It might be also considered as a confirmation of declared gender in web-based surveys. Social implications As not all users perceive personalised ads and websites as beneficial, this application requires the analysis of a user perspective to provide value to the consumer without privacy violation. Originality/value Behavioural characteristics, such as mouse movements and keystroke dynamics, have already been used for user authentication and emotion recognition, but applying these data to gender recognition is an original idea.
Cytowania
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Web of Science
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Autorzy (5)
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Pawel Jarmolkowicz
- Harimata Sp. z o.o. .
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Michal Jarmolkowicz
- Harimata Sp. z o.o. .
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Krzysztof Sobota
- Harimata Sp. z o.o. .
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Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuł w czasopiśmie wyróżnionym w JCR
- Opublikowano w:
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Internet Research
nr 26,
wydanie 5,
strony 1093 - 1111,
ISSN: 1066-2243 - Język:
- angielski
- Rok wydania:
- 2016
- Opis bibliograficzny:
- Kołakowska A., Landowska A., Jarmolkowicz P., Jarmolkowicz M., Sobota K.: Automatic recognition of males and females among web browser users based on behavioural patterns of peripherals usage// Internet Research. -Vol. 26, iss. 5 (2016), s.1093-1111
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1108/intr-04-2015-0100
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 161 razy