Arko Ghosh | Searcharxiv

arXiv2020

A generalized priority-based model for smartphone screen touches

The distribution of intervals between human actions such as email posts or keyboard strokes demonstrates distinct properties at short vs long time scales. For instance, at long time scales, which are presumably controlled by complex process such as planning and decision making, it has been shown that those inter-event intervals follow a scale-invariant (or power-law) distribution. In contrast, at shorter time-scales - which are governed by different process such as sensorimotor skill - they do not follow the same distribution and little do we know how they relate to the scale-invariant pattern. Here, we analyzed 9 millions intervals between smartphone screen touches of 84 individuals which span several orders of magnitudes (from milliseconds to hours). To capture these intervals, we extend a priority-based generative model to smartphone touching events. At short-time scale, the model is governed by refractory effects, while at longer time scales, the inter-touch intervals are governed by the priority difference between smartphone tasks and other tasks. The flexibility of the model allows to capture inter-individual variations at short and long time scales while its tractability enables efficient model fitting. According to our model, each individual has a specific power-low exponent which is tightly related to the effective refractory time constant suggesting that motor processes which influence the fast actions are related to the higher cognitive processes governing the longer inter-event intervals.

cs.SI↗

arXiv2017

Optimised information gathering in smartphone users

Human activities from hunting to emailing are performed in a fractal-like scale invariant pattern. These patterns are considered efficient for hunting or foraging, but are they efficient for gathering information? Here we link the scale invariant pattern of inter-touch intervals on the smartphone to optimal strategies for information gathering. We recorded touchscreen touches in 65 individuals for a month and categorized the activity into checking for information vs. sharing content. For both categories, the inter-touch intervals were well described by power-law fits spanning 5 orders of magnitude, from 1 s to several hours. The power-law exponent typically found for checking was 1.5 and for generating it was 1.3. Next, by using computer simulations we addressed whether the checking pattern was efficient - in terms of minimizing futile attempts yielding no new information. We find that the best performing power law exponent depends on the duration of the assessment and the exponent of 1.5 was the most efficient in the short-term i.e. in the few minutes range. Finally, we addressed whether how people generated and shared content was in tune with the checking pattern. We assumed that the unchecked posts must be minimized for maximal efficiency and according to our analysis the most efficient temporal pattern to share content was the exponent of 1.3 - which was also the pattern displayed by the smartphone users. The behavioral organization for content generation is different from content consumption across time scales. We propose that this difference is a signature of optimal behavior and the short-term assessments used in modern human actions.

physics.soc-ph↗