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Entropy 2016, 18(8), 296; doi:10.3390/e18080296

Temporal Predictability of Online Behavior in Foursquare

School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
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Academic Editor: Raúl Alcaraz Martínez
Received: 16 June 2016 / Revised: 2 August 2016 / Accepted: 8 August 2016 / Published: 12 August 2016
(This article belongs to the Section Information Theory)
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Abstract

With the widespread use of Internet technologies, online behaviors play a more and more important role in humans’ daily lives. Knowing the times when humans perform their next online activities can be quite valuable for developing better online services, which prompts us to wonder whether the times of users’ next online activities are predictable. In this paper, we investigate the temporal predictability in human online activities through exploiting the dataset from the social network Foursquare. Through discretizing the inter-event times of users’ Foursquare activities into symbols, we map each user’s inter-event time sequence to a sequence of inter-event time symbols. By applying the information-theoretic method to the sequences of inter-event time symbols, we show that for a user’s Foursquare activities, knowing the time interval between the current activity and the previous activity decreases the entropy of the time interval between the next activity and current activity, i.e., the time of the user’s next Foursquare activity is predictable. Much of the predictability is explained by the equal-interval repeat; that is, users perform consecutive Foursquare activities with approximately equal time intervals. On the other hand, the unequal-interval preference, i.e., the preference of performing Foursquare activities with a fixed time interval after another given time interval, is also an origin for predictability. Furthermore, our results reveal that the Foursquare activities on weekdays have a higher temporal predictability than those on weekends and that users’ Foursquare activity is more temporally predictable if his/her previous activity is performed in a location that he/she visits more frequently. View Full-Text
Keywords: entropy; human dynamic; online activity; temporal predictability; social network entropy; human dynamic; online activity; temporal predictability; social network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, W.; Gao, Q.; Xiong, H. Temporal Predictability of Online Behavior in Foursquare. Entropy 2016, 18, 296.

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