How does priming influence people's decision? Quantitative analysis of EEG and eye movement II
The basic principle of priming involves stimulation of sensitivity to certain stimuli due to previous exposure to related stimulus. Such priming effects could possibly influence attitude and evaluation towards an image. In the realm of advertising, a successful product evaluation would likely depend...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/52961 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-52961 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-529612023-07-07T15:51:04Z How does priming influence people's decision? Quantitative analysis of EEG and eye movement II Soh, Wee Liang. School of Electrical and Electronic Engineering DSO National Laboratories Justin Dauwels DRNTU::Engineering::Electrical and electronic engineering DRNTU::Engineering::Bioengineering The basic principle of priming involves stimulation of sensitivity to certain stimuli due to previous exposure to related stimulus. Such priming effects could possibly influence attitude and evaluation towards an image. In the realm of advertising, a successful product evaluation would likely depend on careful selection of primes. Current popular methods in evaluating priming effect of consumers’ attitude and intention, such as self-evaluation questionnaires, are not standardized and effective. In this project, the influence of subliminal priming on subjects’ perception of visual stimuli and decision-making by quantitative analysis of ERPs was studied. EEG data was acquired from forty subjects across three different priming conditions. The data mining process, includes signal enhancement, component analysis, feature selection and discriminant analysis, was applied in the study. The study compared normal averaging and Woody averaging techniques to investigate the latency jitters effect. In particular, windowed mean amplitude was applied for component analysis. The study focused on latency at early window, N100, and late window, P300 for evaluation involved in perception and decision-making process respectively. In particular, normal averaged ERP yielded significant results in the component analysis. Further study was carried out using SVM binary and multi-class classifier. Highest results of classification of priming conditions were obtained from the features selection studied earlier. Hence, it is evident that priming effect is influential to subjects’ evaluation of image or advertisement with the encouraging results of the component analysis and classification in line with previous literature. Bachelor of Engineering 2013-05-29T05:51:21Z 2013-05-29T05:51:21Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52961 en Nanyang Technological University 117 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Electrical and electronic engineering DRNTU::Engineering::Bioengineering |
spellingShingle |
DRNTU::Engineering::Electrical and electronic engineering DRNTU::Engineering::Bioengineering Soh, Wee Liang. How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
description |
The basic principle of priming involves stimulation of sensitivity to certain stimuli due to previous exposure to related stimulus. Such priming effects could possibly influence attitude and evaluation towards an image. In the realm of advertising, a successful product evaluation would likely depend on careful selection of primes. Current popular methods in evaluating priming effect of consumers’ attitude and intention, such as self-evaluation questionnaires, are not standardized and effective. In this project, the influence of subliminal priming on subjects’ perception of visual stimuli and decision-making by quantitative analysis of ERPs was studied. EEG data was acquired from forty subjects across three different priming conditions. The data mining process, includes signal enhancement, component analysis, feature selection and discriminant analysis, was applied in the study. The study compared normal averaging and Woody averaging techniques to investigate the latency jitters effect. In particular, windowed mean amplitude was applied for component analysis. The study focused on latency at early window, N100, and late window, P300 for evaluation involved in perception and decision-making process respectively. In particular, normal averaged ERP yielded significant results in the component analysis. Further study was carried out using SVM binary and multi-class classifier. Highest results of classification of priming conditions were obtained from the features selection studied earlier. Hence, it is evident that priming effect is influential to subjects’ evaluation of image or advertisement with the encouraging results of the component analysis and classification in line with previous literature. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Soh, Wee Liang. |
format |
Final Year Project |
author |
Soh, Wee Liang. |
author_sort |
Soh, Wee Liang. |
title |
How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
title_short |
How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
title_full |
How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
title_fullStr |
How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
title_full_unstemmed |
How does priming influence people's decision? Quantitative analysis of EEG and eye movement II |
title_sort |
how does priming influence people's decision? quantitative analysis of eeg and eye movement ii |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/52961 |
_version_ |
1772826562310176768 |