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Article
Publication date: 4 September 2019

Agnieszka Landowska

The purpose of this paper is to explore uncertainty inherent in emotion recognition technologies and the consequences resulting from that phenomenon.

Abstract

Purpose

The purpose of this paper is to explore uncertainty inherent in emotion recognition technologies and the consequences resulting from that phenomenon.

Design/methodology/approach

The paper is a general overview of the concept; however, it is based on a meta-analysis of multiple experimental and observational studies performed over the past couple of years.

Findings

The main finding of the paper might be summarized as follows: there is uncertainty inherent in emotion recognition technologies, and the phenomenon is not expressed enough, not addressed enough and unknown by the users of the technology.

Practical implications

Practical implications of the study are formulated as postulates for the developers, users and researchers dealing with the technologies of automatic emotion recognition.

Social implications

As technologies that recognize emotions are becoming more and more common, and perhaps more decisions influencing people lives are to come in the next decades, the trustworthiness of the technology is important from a scientific, practical and ethical point of view.

Originality/value

Studying uncertainty of emotion recognition technologies is a novel approach and is not explored from such a broad perspective before.

Details

Journal of Information, Communication and Ethics in Society, vol. 17 no. 3
Type: Research Article
ISSN: 1477-996X

Keywords

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Article
Publication date: 3 October 2016

Agata Kolakowska, Agnieszka Landowska, Pawel Jarmolkowicz, Michal Jarmolkowicz and Krzysztof Sobota

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.

Abstract

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.

Details

Internet Research, vol. 26 no. 5
Type: Research Article
ISSN: 1066-2243

Keywords

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Article
Publication date: 17 September 2019

Katleen Gabriels

This study responds to Agnieszka Landowska’s paper about the lack of accuracy in emotion recognition.

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Abstract

Purpose

This study responds to Agnieszka Landowska’s paper about the lack of accuracy in emotion recognition.

Design/methodology/approach

The approach is purely theoretical. The paper also refers to empirical studies.

Findings

The author first elaborates on Landowska’s “postulates” (normative guidelines) and then shortly expands on how virtual chatbots such as “AI therapists” pose considerable challenges to emotion recognition algorithms as well.

Originality/value

This viewpoint’s value is to elaborate and expand on an ongoing discussion on emotion recognition technologies.

Details

Journal of Information, Communication and Ethics in Society, vol. 17 no. 3
Type: Research Article
ISSN: 1477-996X

Keywords

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