Differences in smartphone usage: validating, evaluating, and predicting mobile user intimacy
Research output: Contribution to journal › Journal article › Research › peer-review
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Differences in smartphone usage : validating, evaluating, and predicting mobile user intimacy. / Gustarini, Mattia; Scipioni, Marcello Paolo; Fanourakis, Marios; Wac, Katarzyna.
In: Pervasive and Mobile Computing, Vol. 33, 2016, p. 50-72.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Differences in smartphone usage
T2 - validating, evaluating, and predicting mobile user intimacy
AU - Gustarini, Mattia
AU - Scipioni, Marcello Paolo
AU - Fanourakis, Marios
AU - Wac, Katarzyna
PY - 2016
Y1 - 2016
N2 - We analyze the users’ intimacy to investigate the differences in smartphone usage, considering the user’s location and number and kind of people physically around the user. With a first user study we (1) validate the intimacy concept, (2) evaluate its correlation to smartphone usage features and (3) we computationally model it. Shorter, more frequent, and less engaging interactions take place when intimacy is lower, while longer, less frequent, and engaging interactions when intimacy is higher. With a second user study, we investigate the intimacy predictability in practice. Location-time features are predictive for the intimacy, and other smartphone-based features can improve the intimacy prediction accuracy.
AB - We analyze the users’ intimacy to investigate the differences in smartphone usage, considering the user’s location and number and kind of people physically around the user. With a first user study we (1) validate the intimacy concept, (2) evaluate its correlation to smartphone usage features and (3) we computationally model it. Shorter, more frequent, and less engaging interactions take place when intimacy is lower, while longer, less frequent, and engaging interactions when intimacy is higher. With a second user study, we investigate the intimacy predictability in practice. Location-time features are predictive for the intimacy, and other smartphone-based features can improve the intimacy prediction accuracy.
U2 - 10.1016/j.pmcj.2016.06.003
DO - 10.1016/j.pmcj.2016.06.003
M3 - Journal article
VL - 33
SP - 50
EP - 72
JO - Pervasive and Mobile Computing
JF - Pervasive and Mobile Computing
SN - 1574-1192
ER -
ID: 166605857