Name
Title | ||
|---|---|---|
Predicting Online Shopping Search Satisfaction and User Behaviors with Electrodermal Activity. |
Abstract | ||
|---|---|---|
Electrodermal activity (EDA) delineates positive and negative emotions, especially in the lower arousal range, which reflects small variations. This study derived formulas to extract features from the EDA graph and found they are effective to predict search satisfaction and explain mobile shopping behaviors including add to cart, purchase, and abandonment (added to cart without purchase). The best features found in the generalized linear mixed model with the binomial family agree with known physiological results. To the best of our knowledge, this study is the first to use physiological methods to study satisfaction and user behavior. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3041021.3054226 | WWW (Companion Volume) |
Field | DocType | Citations |
Arousal,Graph,Data mining,Cart,Computer science,Binomial,Generalized linear mixed model | Conference | 2 |
PageRank | References | Authors |
0.36 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingying Wu | 1 | 13 | 1.88 |
| Yiqun Liu | 2 | 1592 | 136.51 |
| Ning Su | 3 | 23 | 3.63 |
| Shaoping Ma | 4 | 1544 | 126.00 |
| Wenwu Ou | 5 | 191 | 15.56 |