Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists’ Responses to Traditional Village Landscapes
Abstract
:1. Introduction
2. Related Works
3. Research Methodology and Experimental Design
- (1)
- What are the relationships between eye-tracking metrics (APD, ANS, TDF, FC) and tourists’ emotional experiences (positive, neutral, and negative) in the context of traditional village landscapes?
- (2)
- How do the interactions between tour phases (entry, core, and departure) and landscape types (historical, architectural, economic, and life) influence eye-tracking metrics and, consequently, emotional experiences?
- (3)
- Can a prediction model be developed using eye-tracking data and machine learning techniques to accurately capture and predict the dynamic emotional responses of tourists to cultural landscapes, ultimately contributing to sustainable village development and enhanced visitor experiences?
3.1. Study Area
3.2. Experimental Design
3.2.1. Stimuli
3.2.2. Participants
3.2.3. Procedure
3.2.4. Data Processing and Analysis
4. Results
4.1. Eye-Tracking Metrics across Different Phases and Landscape Types
4.2. Eye-Tracking Metrics in Each Phases and Landscape Types
4.3. Correlation Testing between Eye-Tracking Experiment Data and Emotional Evaluation
4.4. Landscape-Specific Emotional Prediction Models
4.4.1. Historic Landscapes and Positive Emotional Prediction
4.4.2. Architectural Landscapes and Neutral Emotional Prediction
4.4.3. Economic Landscapes and Negative Emotional Prediction
4.5. Model Validation Test
5. Discussion
5.1. Advancing Eye-Tracking and Emotion Prediction in Tourism
5.2. Implications for Cultural Landscape Planning and Tourism Design
5.3. Limitations and Future Research Directions
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Entry Phase | Core Phase | Departure Phases | |
---|---|---|---|
Historical Landscape | |||
Architectural Landscape | |||
Economic Landscape | |||
Life Landscape |
Eye-Tracking Metrics | Meaning |
---|---|
Average Number of Saccades (ANS) | The number of times the observer gazes during a specific period of time. Generally, a higher number of gazes may indicate higher visual or cognitive processing demands. |
Total Fixation Duration (TDF) | Total time observed by the observer. Reflects greater attractiveness or richer information for the observer. |
Fixation Count (FC) | The number of times the observer gazes. Multiple gazes may indicate repeated attention from the observer. |
APD | It is generally considered as an indicator of emotional arousal and cognitive load. An increase in pupil diameter is usually associated with high levels of emotional arousal or cognitive load. |
Eye-Tracking Metrics | Effect | SS | df | MS | F | p | ηp2 |
---|---|---|---|---|---|---|---|
ANS | Tour Phase | 1.257 | 2 | 0.628 | 0.457 | 0.635 | 0.012 |
Landscape Type | 27.503 | 3 | 9.168 | 6.556 | <0.001 *** | 0.144 | |
Tour Phase × Landscape Type | 17.721 | 6 | 2.954 | 2.225 | 0.042 * | 0.054 | |
TDF | Tour Phase | 0.152 | 2 | 0.076 | 0.756 | 0.473 | 0.019 |
Landscape Type | 0.727 | 3 | 0.242 | 2.362 | 0.075 | 0.057 | |
Tour Phase × Landscape Type | 1.769 | 6 | 0.295 | 2.494 | 0.023 * | 0.06 | |
FC | Tour Phase | 21.975 | 2 | 10.988 | 4.521 | 0.014 * | 0.104 |
Landscape Type | 9.495 | 3 | 3.165 | 1.269 | 0.288 | 0.032 | |
Tour Phase × Landscape Type | 43.866 | 6 | 7.311 | 2.85 | 0.011 * | 0.068 | |
APD | Tour Phase | 2.54 | 2 | 1.27 | 2.268 | 0.11 | 0.055 |
Landscape Type | 13.231 | 3 | 4.41 | 7.46 | <0.001 *** | 0.161 | |
Tour Phase × Landscape Type | 4.926 | 6 | 0.821 | 1.327 | 0.246 | 0.033 |
ANS | TDF | |||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Entry Phase | Core Phase | Departure Phase | Entry Phase | Core Phase | Departure Phase | |||||||||||||
M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | |
Architectural Landscapes | 3.18 | 1.22 | 2.791–3.57 | 2.83 | 1.1 | 2.474–3.179 | 3.29 | 1.03 | 2.961–3.621 | 0.60 | 0.33 | 0.496–0.709 | 0.76 | 0.31 | 0.656–0.856 | 0.69 | 0.36 | 0.577–0.804 |
Historical Landscape | 3.23 | 1.27 | 2.825–3.635 | 2.56 | 1.06 | 2.219–2.896 | 2.78 | 1.25 | 2.383–3.182 | 0.68 | 0.39 | 0.557–0.807 | 0.78 | 0.32 | 0.682–0.884 | 0.70 | 0.33 | 0.593–0.806 |
Economic Landscape | 2.43 | 1.11 | 2.074–2.781 | 2.67 | 1.31 | 2.25–3.086 | 2.51 | 1.17 | 2.138–2.888 | 0.65 | 0.33 | 0.544–0.754 | 0.55 | 0.27 | 0.466–0.639 | 0.67 | 0.35 | 0.562–0.787 |
Life Landscape | 2.28 | 0.96 | 1.973–2.587 | 2.68 | 1.37 | 2.241–3.121 | 2.62 | 1.13 | 2.254–2.979 | 0.69 | 0.27 | 0.603–0.775 | 0.51 | 0.34 | 0.405–0.62 | 0.70 | 0.34 | 0.592–0.807 |
F(6, 234) = 2.225, p < 0.05, ηp2 = 0.054 | F(6, 234) = 2.494, p < 0.05, ηp2 = 0.06 | |||||||||||||||||
FC | APD | |||||||||||||||||
Entry Phase | Core Phase | Departure Phase | Entry Phase | Core Phase | Departure Phase | |||||||||||||
M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | M | SD | 95%CI | |
Architectural Landscapes | 3.39 | 1.62 | 2.869–3.908 | 4.38 | 1.63 | 3.857–4.901 | 3.17 | 1.35 | 2.737–3.602 | 3.04 | 0.84 | 2.776–3.311 | 3.12 | 0.75 | 2.879–3.36 | 2.71 | 0.76 | 2.463–2.951 |
Historical Landscape | 3.45 | 1.64 | 2.926–3.977 | 4.49 | 1.63 | 3.97–5.014 | 3.57 | 1.65 | 3.043–4.099 | 2.97 | 0.71 | 2.742–3.193 | 2.89 | 0.7 | 2.67–3.12 | 2.67 | 0.83 | 2.402–2.934 |
Economic Landscape | 3.6 | 1.45 | 3.136–4.061 | 3.51 | 1.42 | 3.056–3.965 | 3.64 | 1.69 | 3.103–4.186 | 2.7 | 0.84 | 2.429–2.967 | 2.56 | 0.77 | 2.312–2.804 | 2.49 | 0.86 | 2.213–2.764 |
Life Landscape | 3.26 | 1.77 | 2.69–3.823 | 3.31 | 1.35 | 2.883–3.746 | 3.77 | 1.89 | 3.164–4.376 | 2.5 | 0.73 | 2.265–2.733 | 2.54 | 0.59 | 2.351–2.726 | 2.68 | 0.79 | 2.43–2.938 |
F(6, 234) = 2.85, p < 0.05, ηp2 = 0.068 | / |
Positive Emotions | Negative Emotions | Neutral Emotions | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Eye-Tracking Metrics | ANS | TDF | FC | APD | ANS | TDF | FC | APD | ANS | TDF | FC | APD | |
Entry Phase | Architectural Landscapes | 0.041 | −0.083 | −0.159 | 0.232 | 0.348 * | 0.179 | 0.035 | −0.044 | −0.08 | 0.028 | −0.02 | −0.086 |
Historic Landscapes | −0.221 | 0.073 | −0.197 | 0.527 ** | −0.08 | −0.077 | 0.044 | 0.118 | −0.183 | 0.003 | 0.143 | 0.033 | |
Economic Landscapes | −0.07 | 0.069 | −0.062 | −0.193 | −0.242 | 0.046 | 0.198 | −0.079 | −0.256 | 0.348 * | 0.013 | −0.02 | |
Life Landscapes | 0.161 | −0.034 | 0.315 * | 0.054 | 0.109 | −0.092 | −0.181 | −0.021 | 0.078 | −0.086 | −0.054 | 0.21 | |
Core Phase | Architectural Landscapes | −0.053 | 0.141 | −0.175 | −0.125 | 0.035 | −0.197 | −0.676 ** | −0.13 | −0.237 | −0.18 | 0.016 | −0.218 |
Historic Landscapes | −0.589 ** | 0.605 ** | 0.147 | 0.447 ** | 0.051 | 0.037 | −0.033 | 0.038 | 0.082 | −0.175 | −0.322 * | −0.212 | |
Economic Landscapes | 0.093 | −0.048 | 0.173 | −0.023 | −0.065 | 0.198 | −0.328 * | −0.022 | 0.534 ** | 0.207 | −0.648 ** | −0.449 ** | |
Life Landscapes | 0.058 | −0.343 * | 0.078 | −0.079 | 0.08 | −0.181 | −0.111 | −0.249 | −0.167 | −0.057 | −0.196 | −0.119 | |
Departure Phase | Architectural Landscapes | −0.149 | −0.148 | 0.097 | 0.033 | 0.06 | −0.073 | 0.039 | −0.205 | 0.238 | 0.212 | 0.142 | −0.243 |
Historic Landscapes | −0.268 | −0.064 | 0.279 | 0.182 | 0.052 | 0.112 | −0.126 | 0.267 | 0.146 | −0.277 | −0.268 | 0.085 | |
Economic Landscapes | −0.179 | −0.164 | −0.086 | −0.02 | 0.146 | −0.095 | −0.395 * | 0.016 | 0.226 | −0.087 | −0.138 | −0.329 * | |
Life Landscapes | 0.069 | 0.126 | 0.07 | 0.066 | 0.056 | −0.027 | −0.052 | 0.087 | −0.258 | 0.06 | 0.058 | 0.093 |
Stepwise | B | SE B | β | t | p | |
---|---|---|---|---|---|---|
1 | Constant | 2.346 | 0.252 | 9.322 | <0.001 *** | |
kTFD | 1.398 | 0.298 | 0.605 | 4.683 | <0.001 *** | |
2 | Constant | 3.38 | 0.348 | 9.701 | <0.001 *** | |
kTFD | 1.078 | 0.27 | 0.466 | 3.986 | <0.001 *** | |
kANS | −0.306 | 0.081 | −0.443 | −3.787 | 0.001 ** | |
3 | Constant | 2.312 | 0.325 | 7.122 | <0.001 *** | |
kTFD | 0.735 | 0.211 | 0.318 | 3.479 | 0.001 *** | |
kANS | −0.36 | 0.061 | −0.521 | −5.882 | <0.001 *** | |
eAPD | 0.496 | 0.09 | 0.479 | 5.503 | <0.001 *** | |
4 | Constant | 1.417 | 0.213 | 6.66 | <0.001 *** | |
kTFD | 0.505 | 0.124 | 0.219 | 4.076 | <0.001 *** | |
kANS | −0.417 | 0.036 | −0.604 | −11.702 | <0.001 *** | |
eAPD | 0.475 | 0.052 | 0.459 | 9.186 | <0.001 *** | |
kAPD | 0.444 | 0.051 | 0.427 | 8.644 | <0.001 *** |
Stepwise | B | SE B | β | t | p | |
---|---|---|---|---|---|---|
1 | Constant | 4.602 | 0.307 | 14.985 | <0.001 *** | |
kFC | −0.372 | 0.066 | −0.676 | −5.659 | <0.001 *** | |
2 | Constant | 3.761 | 0.359 | 10.467 | <0.001 *** | |
kFC | −0.379 | 0.058 | −0.688 | −6.571 | <0.001 *** | |
eANS | 0.274 | 0.077 | 0.37 | 3.533 | 0.001 *** | |
3 | Constant | 4.904 | 0.384 | 12.764 | <0.001 *** | |
kFC | −0.404 | 0.047 | −0.733 | −8.602 | <0.001 *** | |
eANS | 0.349 | 0.065 | 0.472 | 5.391 | <0.001 *** | |
lAPD | −0.471 | 0.104 | −0.4 | −4.544 | <0.001 *** |
Stepwise | B | SE B | β | t | p | |
1 | (Constant) | 4.888 | 0.353 | 13.863 | <0.001 *** | |
kFC | −0.489 | 0.093 | −0.648 | −5.248 | <0.001 *** | |
2 | (Constant) | 3.719 | 0.311 | 11.953 | <0.001 *** | |
kFC | −0.497 | 0.066 | −0.659 | −7.552 | <0.001 *** | |
kANS | 0.449 | 0.072 | 0.546 | 6.262 | <0.001 *** | |
3 | (Constant) | 4.719 | 0.329 | 14.354 | <0.001 *** | |
kFC | −0.495 | 0.053 | −0.656 | −9.396 | <0.001 *** | |
kANS | 0.449 | 0.057 | 0.547 | 7.836 | <0.001 *** | |
lAPD | −0.405 | 0.087 | −0.325 | −4.661 | <0.001 *** | |
4 | (Constant) | 5.865 | 0.25 | 23.498 | <0.001 *** |
Tested Model | Average Scores | Model Predicted Scores | Score Difference |
---|---|---|---|
Model (1) | 3.412 | 3.173 | 0.239 |
Model (2) | 3.417 | 3.265 | 0.152 |
Model (3) | 3.521 | 3.092 | 0.429 |
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Ye, F.; Yin, M.; Cao, L.; Sun, S.; Wang, X. Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists’ Responses to Traditional Village Landscapes. Sensors 2024, 24, 4459. https://doi.org/10.3390/s24144459
Ye F, Yin M, Cao L, Sun S, Wang X. Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists’ Responses to Traditional Village Landscapes. Sensors. 2024; 24(14):4459. https://doi.org/10.3390/s24144459
Chicago/Turabian StyleYe, Feng, Min Yin, Leilei Cao, Shouqian Sun, and Xuanzheng Wang. 2024. "Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists’ Responses to Traditional Village Landscapes" Sensors 24, no. 14: 4459. https://doi.org/10.3390/s24144459
APA StyleYe, F., Yin, M., Cao, L., Sun, S., & Wang, X. (2024). Predicting Emotional Experiences through Eye-Tracking: A Study of Tourists’ Responses to Traditional Village Landscapes. Sensors, 24(14), 4459. https://doi.org/10.3390/s24144459