Table 1 Summary of call prediction studies including dataset, evaluation method, prediction accuracy, and predicted channel i.e. call, text, or both. Here, it can be clearly seen that all proposed algorithms so far only target a single channel, i.e. calls
From: Text and phone calls: user behaviour and dual-channel communication prediction
Study | Dataset | Evaluation matrics | Channel | |
|---|---|---|---|---|
Call | Text | |||
Phithakkitnu-koon et al. | (94) Users reality mining project | Accuracy 70% | \(\checkmark \) | \(\times \) |
Phithakkitnu-koon et al. | (20) Users | False positive = 2.4% false negative = 2.9% error rate= 5.4% | \(\checkmark \) | \(\times \) |
Haddad et al. | (7645) users | Mean absolute error = 69 proportion of calls predicted within less than 1h = 17.4 % | \(\checkmark \) | \(\times \) |
Barzaiq et al. | Synthetic data (1, 143) calls reality mining (5, 484) calls | Accuracy 35% | \(\checkmark \) | \(\times \) |
Nasim et al. | Smartphone (786) users reality mining | Accuracy 78% | \(\checkmark \) | \(\times \) |
Stefanis et al. | Reality mining project | Accuracy 80% | \(\checkmark \) | \(\times \) |
Lee et al. | (20) users | Accuracy: group A > 75% other users < 50% | \(\checkmark \) | \(\times \) |
Sarker et al. | Reality mining (5) users | F-measure 0.8 | \(\checkmark \) | \(\times \) |
Fatima et al. | Smartphone (786) users MDC (522) users | Accuracy: MDC 85% Smartphone 56% | \(\checkmark \) | \(\times \) |