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Using Support Vector Machine on EEG for Advertisement Impact Assessment
by
Wu, Chao
, Supratak, Akara
, Guo, Yike
, Wang, Pan
, Wei, Zhen
, Wang, Xiaoyi
in
advertisement impact assessment
/ Biometrics
/ EEG
/ Experimental psychology
/ Focus groups
/ machine learning
/ Marketing
/ neuromarketing
/ Neuroscience
/ Neurosciences
/ Preferences
/ Questionnaires
/ SVM
2018
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Using Support Vector Machine on EEG for Advertisement Impact Assessment
by
Wu, Chao
, Supratak, Akara
, Guo, Yike
, Wang, Pan
, Wei, Zhen
, Wang, Xiaoyi
in
advertisement impact assessment
/ Biometrics
/ EEG
/ Experimental psychology
/ Focus groups
/ machine learning
/ Marketing
/ neuromarketing
/ Neuroscience
/ Neurosciences
/ Preferences
/ Questionnaires
/ SVM
2018
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Do you wish to request the book?
Using Support Vector Machine on EEG for Advertisement Impact Assessment
by
Wu, Chao
, Supratak, Akara
, Guo, Yike
, Wang, Pan
, Wei, Zhen
, Wang, Xiaoyi
in
advertisement impact assessment
/ Biometrics
/ EEG
/ Experimental psychology
/ Focus groups
/ machine learning
/ Marketing
/ neuromarketing
/ Neuroscience
/ Neurosciences
/ Preferences
/ Questionnaires
/ SVM
2018
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Using Support Vector Machine on EEG for Advertisement Impact Assessment
Journal Article
Using Support Vector Machine on EEG for Advertisement Impact Assessment
2018
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Overview
The advertising industry depends on an effective assessment of the impact of advertising as a key performance metric for their products. However, current assessment methods have relied on either indirect inference from observing changes in consumer behavior after the launch of an advertising campaign, which has long cycle times and requires an ad campaign to have already have been launched (often meaning costs having been sunk). Or through surveys or focus groups, which have a potential for experimental biases, peer pressure, and other psychological and sociological phenomena that can reduce the effectiveness of the study. In this paper, we investigate a new approach to assess the impact of advertisement by utilizing low-cost EEG headbands to record and assess the measurable impact of advertising on the brain. Our evaluation shows the desired performance of our method based on user experiment with 30 recruited subjects after watching 220 different advertisements. We believe the proposed SVM method can be further developed to a general and scalable methodology that can enable advertising agencies to assess impact rapidly, quantitatively, and without bias.
Publisher
Frontiers Research Foundation,Frontiers Media S.A
Subject
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