arXiv subjects

Zbigniew Smoreda

Publications and source records attributed to Zbigniew Smoreda.

22 records · Page 2Linked to original sources

arXiv2013

Chatty Mobiles:Individual mobility and communication patterns

Human mobility analysis is an important issue in social sciences, and mobility data are among the most sought-after sources of information in ur- Data ban studies, geography, transportation and territory management. In network sciences mobility studies have become popular in the past few years, especially using mobile phone location data. For preserving the customer privacy, datasets furnished by telecom operators are anonymized. At the same time, the large size of datasets often makes the task of calculating all observed trajectories very difficult and time-consuming. One solution could be to sample users. However, the fact of not having information about the mobile user makes the sampling delicate. Some researchers select randomly a sample of users from their dataset. Others try to optimize this method, for example, taking into account only users with a certain number or frequency of locations recorded. At the first glance, the second choice seems to be more efficient: having more individual traces makes the analysis more precise. However, the most frequently used CDR data (Call Detail Records) have location generated only at the moment of communication (call, SMS, data connection). Due to this fact, users mobility patterns cannot be precisely built upon their communication patterns. Hence, these data have evident short-comings both in terms of spatial and temporal scale. In this paper we propose to estimate the correlation between the users communication and mo- bility in order to better assess the bias of frequency based sampling. Using technical GSM network data (including communication but also independent mobility records), we will analyze the relationship between communication and mobility patterns.

cs.CY↗

arXiv2012

Exploring the Mobility of Mobile Phone Users

Mobile phone datasets allow for the analysis of human behavior on an unprecedented scale. The social network, temporal dynamics and mobile behavior of mobile phone users have often been analyzed independently from each other using mobile phone datasets. In this article, we explore the connections between various features of human behavior extracted from a large mobile phone dataset. Our observations are based on the analysis of communication data of 100000 anonymized and randomly chosen individuals in a dataset of communications in Portugal. We show that clustering and principal component analysis allow for a significant dimension reduction with limited loss of information. The most important features are related to geographical location. In particular, we observe that most people spend most of their time at only a few locations. With the help of clustering methods, we then robustly identify home and office locations and compare the results with official census data. Finally, we analyze the geographic spread of users' frequent locations and show that commuting distances can be reasonably well explained by a gravity model.

physics.soc-ph↗

arXiv2011

Interplay between telecommunications and face-to-face interactions - a study using mobile phone data

In this study we analyze one year of anonymized telecommunications data for over one million customers from a large European cellphone operator, and we investigate the relationship between people's calls and their physical location. We discover that more than 90% of users who have called each other have also shared the same space (cell tower), even if they live far apart. Moreover, we find that close to 70% of users who call each other frequently (at least once per month on average) have shared the same space at the same time - an instance that we call co-location. Co-locations appear indicative of coordination calls, which occur just before face-to-face meetings. Their number is highly predictable based on the amount of calls between two users and the distance between their home locations - suggesting a new way to quantify the interplay between telecommunications and face-to-face interactions.

physics.soc-ph↗

arXiv2008

Geographical dispersal of mobile communication networks

In this paper, we analyze statistical properties of a communication network constructed from the records of a mobile phone company. The network consists of 2.5 million customers that have placed 810 millions of communications (phone calls and text messages) over a period of 6 months and for whom we have geographical home localization information. It is shown that the degree distribution in this network has a power-law degree distribution $k^{-5}$ and that the probability that two customers are connected by a link follows a gravity model, i.e. decreases like $d^{-2}$, where $d$ is the distance between the customers. We also consider the geographical extension of communication triangles and we show that communication triangles are not only composed of geographically adjacent nodes but that they may extend over large distances. This last property is not captured by the existing models of geographical networks and in a last section we propose a new model that reproduces the observed property. Our model, which is based on the migration and on the local adaptation of agents, is then studied analytically and the resulting predictions are confirmed by computer simulations.

physics.soc-ph↗