@inproceedingsHen2011, Author = {Henze, Niels and Boll, Susanne and }, Title = {It does not Fitts my data! Analysing large amounts of mobile touch data}, Year = {2011}, Month = {09}, Booktitle = {Proceedings of Interact}, type = {inproceedings}, note = {Touchscreens are the dominant input device for smartphones and learning about smartphone users' touch behaviour became even more important. We developed a game for Android phones to collect a truly large amount of touch data from diverse devices and playe}, Abstract = {Touchscreens are the dominant input device for smartphones and learning about smartphone users' touch behaviour became even more important. We developed a game for Android phones to collect a truly large amount of touch data from diverse devices and players. A part of the game is designed as what we expected to be a Fitts' law task. By publishing the game in the Android Market we collected 5,359,650 micro tasks from 63,154 installations of the game. Using Fitts' law to find a model for these tasks we found a very weak correlation and an implausible high index of performance across different devices. Further analysis shows a similar correlation between time and distance as with Fitts' law but only a very weak correlation with the targets' width.} @COMMENTBibtex file generated on