Table 6 Summary of the used systems for implicit modeling of personality
Systems | Learning | Fun | Traces | Personality Model | Data Analysis Method | Accuracy |
|---|---|---|---|---|---|---|
Virtual Personality Assessment Lab (Bunian et al. 2018) | – | + | Gaming behavior | FFM | Hidden Markov Models (HMM), Baum-Welch algorithm | From 54.1% to 59.1% |
Psyops (Tekofsky et al. 2013) | – | + | Gaming behavior | FFM | Not mentioned | Not mentioned |
Handwriting (Chen and Lin 2017) | – | – | Hand-writing | Not mentioned | Support Vector Machine, k-Nearest Neighbour, AdaBoost and Artificial Neural Network | From 62.5% to 83.9% |
MOOC (Chen et al. 2016) | + | – | Learning | FFM | Gaussian Process and Random Forest | Not mentioned |
Facebook (Buettner 2017). | – | – | Social network | FFM | Generalized linear modeling | From 62% to 71% |
Twitter (Golbeck et al. 2011) | – | – | Social network | FFM | ZeroR and Gaussian Processes | Not mentioned |
Electronically Activated Recorder (Mairesse et al. 2007) | – | – | Speech | FFM | Naive Bayes, AdaboostM1 and Support vector machines | From 51.45% to 62.52% |
Smart phones (Chittaranjan et al. 2011) | – | – | Smart phone | FFM | SVM and C4.5 classifiers | From 59.8% to 75.9% |
E-learning system (Ghorbani and Montazer 2015) | + | – | Learning | FFM | Fuzzy logic | From 78% to 97% |
Wearable sensors (Olguın et al. 2009) | – | – | Sensors | FFM | Accelerometer signal, IR transmissions, RSSI (radio signal strength indicator), | Not mentioned |
Our framework (CAG + LA system) | + | + | Gaming behavior | FFM | Naïve Bayes classifier | From 70.58% to 79.41% |