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Article
Publication date: 29 January 2018

Alexa K. Fox, George D. Deitz, Marla B. Royne and Joseph D. Fox

Online consumer reviews (OCRs) have emerged as a particularly important type of user-generated information about a brand because of their widespread adoption and influence…

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Abstract

Purpose

Online consumer reviews (OCRs) have emerged as a particularly important type of user-generated information about a brand because of their widespread adoption and influence on consumer decision-making. Much of the existing OCR research focuses on quantifiable OCR features such as star ratings and volume. More research that examines the influence of review elements, aside from numeric ratings, such as the verbatim text, particularly in services contexts is needed. The purpose of this research is to investigate the impact of service failures on consumer arousal and emotions.

Design/methodology/approach

The authors present three behavioral experiments that manipulate service failure and linguistic elements of OCRs by using galvanic skin response, survey measures and automated facial expression analysis.

Findings

Negative OCRs lead to the greatest levels of arousal when consumers read OCRs. Service failure severity impacts anger, and referential cohesion, an observable property of text that helps a reader better understand ideas in the text, negatively moderates the relationship between service failure severity and anger.

Originality/value

The authors are among the first to empirically test the effect of emotional contagion in a user-generated content context, demonstrating that it can occur when consumers read such content, even if they did not experience the events being described. The research uses a self-report and physiological measures to assess consumer perceptions, arousal and emotions related to service failures, increasing the robustness of the literature. These findings contribute to the marketing literature on OCRs in service failures, physiological measures of consumers’ emotions, the negativity bias and emotional contagion in a user-generated content context.

Details

European Journal of Marketing, vol. 52 no. 1/2
Type: Research Article
ISSN: 0309-0566

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Book part
Publication date: 13 June 2013

Li Xiao, Hye-jin Kim and Min Ding

Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as…

Abstract

Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing scholars become more aware of the value of audio and visual data and the technologies required to reveal insights into marketing problems. This chapter aims to introduce marketing scholars into this field of research.Design/methodology/approach – This chapter reviews the current technology in audio and visual data analysis and discusses rewarding research opportunities in marketing using these data.Findings – Compared with traditional data like survey and scanner data, audio and visual data provides richer information and is easier to collect. Given these superiority, data availability, feasibility of storage, and increasing computational power, we believe that these data will contribute to better marketing practices with the help of marketing scholars in the near future.Practical implications: The adoption of audio and visual data in marketing practices will help practitioners to get better insights into marketing problems and thus make better decisions.Value/originality – This chapter makes first attempt in the marketing literature to review the current technology in audio and visual data analysis and proposes promising applications of such technology. We hope it will inspire scholars to utilize audio and visual data in marketing research.

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Review of Marketing Research
Type: Book
ISBN: 978-1-78190-761-0

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Article
Publication date: 7 June 2013

Kuan Cheng Lin, Tien‐Chi Huang, Jason C. Hung, Neil Y. Yen and Szu Ju Chen

This study aims to introduce an affective computing‐based method of identifying student understanding throughout a distance learning course.

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1337

Abstract

Purpose

This study aims to introduce an affective computing‐based method of identifying student understanding throughout a distance learning course.

Design/methodology/approach

The study proposed a learning emotion recognition model that included three phases: feature extraction and generation, feature subset selection and emotion recognition. Features are extracted from facial images and transform a given measument of facial expressions to a new set of features defining and computing by eigenvectors. Feature subset selection uses the immune memory clone algorithms to optimize the feature selection. Emotion recognition uses a classifier to build the connection between facial expression and learning emotion.

Findings

Experimental results using the basic expression of facial expression recognition research database, JAFFE, show that the proposed facial expression recognition method has high classification performance. The experiment results also show that the recognition of spontaneous facial expressions is effective in the synchronous distance learning courses.

Originality/value

The study shows that identifying student comprehension based on facial expression recognition in synchronous distance learning courses is feasible. This can help instrutors understand the student comprehension real time. So instructors can adapt their teaching materials and strategy to fit with the learning status of students.

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Book part
Publication date: 15 March 2021

Niels Neudecker, Deepak Varma, David Wright and Robert Powell

Advances in technology over recent years made it possible to use machines and artificial intelligence to develop commercially viable solutions for companies to listen to…

Abstract

Advances in technology over recent years made it possible to use machines and artificial intelligence to develop commercially viable solutions for companies to listen to consumers, decode the meaning, and respond accordingly. In parallel, solutions have been developed that are able to automatically track facial expressions of consumers when reacting to a given marketing stimulus.

The authors look at how marketing executives can apply these technologies to generate enhanced customer insights, providing a realistic context for future applications. The focus is on bringing researchers and managers closer to those moments of truth and our ability to understand customer emotions, emotional reaction, everyday language, and ultimately brand engagement.

The chapter covers the application of commercially viable use cases for (1) the automated measurement of emotions through facial coding to optimize advertizing and content, and (2) the use of voice coding technology to design interactive chatbots as an alternative to traditional surveys. In the outlook, the authors describe the potential that these technologies provide for future research and further use cases.

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The Machine Age of Customer Insight
Type: Book
ISBN: 978-1-83909-697-6

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Article
Publication date: 27 August 2019

Min Hao, Guangyuan Liu, Desheng Xie, Ming Ye and Jing Cai

Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans…

Abstract

Purpose

Happiness is an important mental emotion and yet becoming a major health concern nowadays. For this reason, better recognizing the objective understanding of how humans respond to event-related observations in their daily lives is especially important.

Design/methodology/approach

This paper uses non-intrusive technology (hyperspectral imaging [HSI]) for happiness recognition. Experimental setup is conducted for data collection in real-life environments where observers are showing spontaneous expressions of emotions (calm, happy, unhappy: angry) during the experimental process. Based on facial imaging captured from HSI, this work collects our emotional database defined as SWU Happiness DB and studies whether the physiological signal (i.e. tissue oxygen saturation [StO2], obtained by an optical absorption model) can be used to recognize observer happiness automatically. It proposes a novel method to capture local dynamic patterns (LDP) in facial regions, introducing local variations in facial StO2 to fully use physiological characteristics with regard to hyperspectral patterns. Further, it applies a linear discriminant analysis-based support vector machine to recognize happiness patterns.

Findings

The results show that the best classification accuracy is 97.89 per cent, objectively demonstrating a feasible application of LDP features on happiness recognition.

Originality/value

This paper proposes a novel feature (i.e. LDP) to represent the local variations in facial StO2 for modeling the active happiness. It provides a possible extension to the promising practical application.

Details

Engineering Computations, vol. 37 no. 1
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 6 September 2018

Ihab Zaqout and Mones Al-Hanjori

The face recognition problem has a long history and a significant practical perspective and one of the practical applications of the theory of pattern recognition, to…

Abstract

Purpose

The face recognition problem has a long history and a significant practical perspective and one of the practical applications of the theory of pattern recognition, to automatically localize the face in the image and, if necessary, identify the person in the face. Interests in the procedures underlying the process of localization and individual’s recognition are quite significant in connection with the variety of their practical application in such areas as security systems, verification, forensic expertise, teleconferences, computer games, etc. This paper aims to recognize facial images efficiently. An averaged-feature based technique is proposed to reduce the dimensions of the multi-expression facial features. The classifier model is generated using a supervised learning algorithm called a back-propagation neural network (BPNN), implemented on a MatLab R2017. The recognition rate and accuracy of the proposed methodology is comparable with other methods such as the principle component analysis and linear discriminant analysis with the same data set. In total, 150 faces subjects are selected from the Olivetti Research Laboratory (ORL) data set, resulting 95.6 and 85 per cent recognition rate and accuracy, respectively, and 165 faces subjects from the Yale data set, resulting 95.5 and 84.4 per cent recognition rate and accuracy, respectively.

Design/methodology/approach

Averaged-feature based approach (dimension reduction) and BPNN (generate supervised classifier).

Findings

The recognition rate is 95.6 per cent and recognition accuracy is 85 per cent for the ORL data set, whereas the recognition rate is 95.5 per cent and recognition accuracy is 84.4 per cent for the Yale data set.

Originality/value

Averaged-feature based method.

Details

Information and Learning Science, vol. 119 no. 9/10
Type: Research Article
ISSN: 2398-5348

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Article
Publication date: 30 July 2018

Marzieh Yari Zanganeh and Nadjla Hariri

The purpose of this paper is to identify the role of emotional aspects in information retrieval of PhD students from the web.

Abstract

Purpose

The purpose of this paper is to identify the role of emotional aspects in information retrieval of PhD students from the web.

Design/methodology/approach

From the methodological perspective, the present study is experimental and the type of study is practical. The study population is PhD students of various fields of science. The study sample consists of 50 students as selected by the stratified purposive sampling method. The information aggregation is performed by observing the records of user’s facial expressions, log file by Morae software, as well as pre-search and post-search questionnaire. The data analysis is performed by canonical correlation analysis.

Findings

The findings showed that there was a significant relationship between emotional expressions and searchers’ individual characteristics. Searchers satisfaction of results, frequency internet search, experience of search, interest in the search task and familiarity with similar searches were correlated with the increased happy emotion. The examination of user’s emotions during searching performance showed that users with happiness emotion dedicated much time in searching and viewing of search solutions. More internet addresses with more queries were used by happy participants; on the other hand, users with anger and disgust emotions had the lowest attempt in search performance to complete search process.

Practical implications

The results imply that the information retrieval systems in the web should identify emotional expressions in a set of perceiving signs in human interaction with computer, similarity, face emotional states, searching and information retrieval from the web.

Originality/value

The results explicit in the automatic identification of users’ emotional expressions can enter new dimensions into their moderator and information retrieval systems on the web and can pave the way of design of emotional information retrieval systems for the successful retrieval of users of the network.

Details

Online Information Review, vol. 42 no. 4
Type: Research Article
ISSN: 1468-4527

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Book part
Publication date: 30 September 2020

Gulpreet Kaur Chadha, Seema Rawat and Praveen Kumar

In this chapter, the problem of facial palsy has been addressed. Facial palsy is a term used for disruption of facial muscles and could result in temporary or permanent…

Abstract

In this chapter, the problem of facial palsy has been addressed. Facial palsy is a term used for disruption of facial muscles and could result in temporary or permanent damage of the facial nerve. Patients suffering from facial palsy have issues in doing normal day-to-day activities like eating, drinking, talking, and face psychosocial distress because of their physical appearance. To diagnose and treat facial palsy, the first step is to determine the level of facial paralysis that has affected the patient. This is the most important and challenging step. The research done here proposes how quantitative technology can be used to automate the process of diagnosing the degree of facial paralysis in a fast and efficient way.

Details

Big Data Analytics and Intelligence: A Perspective for Health Care
Type: Book
ISBN: 978-1-83909-099-8

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Article
Publication date: 1 January 2006

Qin Li, King Hong Cheung, Jane You, Raymond Tong and Arthur Mak

Aims to develop an efficient and robust system for real‐time personal identification by automatic face recognition.

Abstract

Purpose

Aims to develop an efficient and robust system for real‐time personal identification by automatic face recognition.

Design/methodology/approach

A wavelet‐based image hierarchy and a guided coarse‐to‐fine search scheme are introduced to improve the computation efficiency in the face detection task. In addition, a Gabor‐based low feature dimensional pattern is proposed to deal with the face recognition problem.

Findings

The proposal of a wavelet‐based image hierarchy and a guided coarse‐to‐fine search scheme is effective to improve the computation efficiency in the face detection task. The introduction of a low feature dimensional pattern is powerful to cope with the transformed appearance‐based face recognition problem. In addition, the use of aggregated Gabor filter responses to represent face images provides a better solution to face feature extraction.

Research limitations/implications

Provides guidance in the design of automatic face recognition system for real‐time personal identification.

Practical implications

Biometrics recognition has been emerging as a new and effective identification technology that attains certain level of maturity. Among many body characteristics that have been used, face is one of the most commonly used characteristics and has drawn considerably large attentions. An automated system to confirm an individual's identity employing features of face is very attractive in many specialized fields.

Originality/value

Introduces a wavelet‐based image hierarchy and a guided coarse‐to‐fine search scheme to improve the computation efficiency in the face detection task. Introduces a Gabor‐based low feature dimensional pattern to deal with the face recognition problem.

Details

Sensor Review, vol. 26 no. 1
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 9 September 2014

Benjamin Wulff, Alexander Fecke, Lisa Rupp and Kai-Christoph Hamborg

The purpose of this work is to present a prototype of the system and the results from a technical evaluation and a study on possible effects of recordings with active…

Abstract

Purpose

The purpose of this work is to present a prototype of the system and the results from a technical evaluation and a study on possible effects of recordings with active camera control on the learner. An increasing number of higher education institutions have adopted the lecture recording technology in the past decade. Even though some solutions already show a very high degree of automation, active camera control can still only be realized with the use of human labor. Aiming to fill this gap, the LectureSight project is developing a free solution for active autonomous camera control for presentation recordings. The system uses a monocular overview camera to analyze the scene. Adopters can formulate camera control strategies in a simple scripting language to adjust the system’s behavior to the specific characteristics of a presentation site.

Design/methodology/approach

The system is based on a highly modularized architecture to make it easily extendible. The prototype has been tested in a seminar room and a large lecture hall. Furthermore, a study was conducted in which students from two universities prepared for a simulated exam with an ordinary lecture recording and a recording produced with the LectureSight technology.

Findings

The technical evaluation showed a good performance of the prototype but also revealed some technical constraints. The results of the psychological study give evidence that the learner might benefit from lecture videos in which the camera follows the presenter so that gestures and facial expression are easily perceptible.

Originality/value

The LectureSight project is the first open-source initiative to care about the topic of camera control for presentation recordings. This opens way for other projects building upon the LectureSight architecture. The simulated exam study gave evidence of a beneficial effect on students learning success and needs to be reproduced. Also, if the effect is proven to be consistent, the mechanism behind it is worth to be investigated further.

Details

Interactive Technology and Smart Education, vol. 11 no. 3
Type: Research Article
ISSN: 1741-5659

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