Human Dynamics on

The dynamic character of our networked society

Sat, 02 Feb 2019 00:00:00 +0000

We live in a networked society and our actions, opinions, behaviors are affected and can affect other people. Understanding such social networked structures is one of the key challenges in our attempt to decode human behavior and its impact in our society. Although human interactions are dynamical by nature, most of our understanding relies in static representations of those social networks. However, social interactions are rarely static. Very often the networks evolve by means of processes that happen at diverse time scales, like link decay/formation, group formation, etc. Our research in the last years have been to develop dynamical models of social networks that account for all those processes at different temporal scales. Understanding how networks evolve has allowed us to reveal new behavior patterns hidden in those social dynamics, but also their effect in societal problems like information diffusion, viral marketing or social mobilization.

For example, using massive datasets of viral marketing campaigns and mobile phone calls by 20 million people, we were the first group to identify the slowing down of information diffusion in social networks due to the inhomogeneous (bursty) activity of humans. This finding explained also why marketing techniques based on spreading of information (viral marketing) are sometimes unsuccessful to achieve expected reach and coverage in reasonable time. But also, it warns us about the potential risk of using network strategies in situations of critical mobilization, a study we published in PNAS: social mobilization can be very fast, but it is unreliable. Part of this research, and specially the understanding of viral marketing campaigns, was recognized by IBM with “2007 Shared University Research” award.

At a different temporal scale, humans create and decay human interactions every day. The unavailability of large longitudinal databases about human interactions prevented the understanding of what are the main strategies behind our social dynamics. In collaboration with Telefónica and accessing the largest dataset (almost two years) used in this kind of research, we were the first group to identify what is the strategy that individuals use to create and decay social relationships while maintaining a constant amount of time/attention to those relationships. We found the universal result that people can be classified as keepers or explorers depending on whether they create less or more relationships for a given capacity to maintain a certain number of relationships. Our finding of those universal strategies have been corroborated by other groups in email or human mobility, for example.

We have worked extensively in this line of research to find how other temporal patterns of social interactions can predict long-term successful relations or the importance of daily rhythms in social relationships. Finally, we have know a collaboration with Facebook to use their data to understand how strong ties are created in our society whether is it possible to predict their creation.

Some recent papers:

Temporal patterns behind the strength of persistent ties
Henry Navarro, Giovanna Miritello, Arturo Canales, Esteban Moro
EPJ Data Science 6 97 (2017)
PDF Journal Altmetric: 35
Twitter session analytics: Profiling users\textquoteright short-term behavioral changes
Farshad Kooti, Esteban Moro, Kristina Lerman
In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2016)
PDF Proceedings Altmetric: 5
Channel-Specific Daily Patterns in Mobile Phone Communication
Talayeh Aledavood, Eduardo Lopez, Sam G B Roberts, Felix Reed-Tsochas, Esteban Moro, Robin I M Dunbar, Jari Saramaki
In Proceedings of ECCS 2014 (2016)
PDF Chapter
Time allocation in social networks: correlation between social structure and human communication dynamics
Giovanna Miritello, Ruben Lara, Esteban Moro
Preprint 175– (2013)
PDF arXiv Altmetric: 7
Limits of social mobilization
Alex Rutherford, Manuel Cebrian, Sohan D’souza, Esteban Moro, Alex Pentland, Iyad Rahwan
Proceedings Of The National Academy Of Sciences Of The United States Of America 110 6281–6286 (2013)
PDF Journal Altmetric: 55
Limited communication capacity unveils strategies for human interaction.
Giovanna Miritello, Ruben Lara, Manuel Cebrian, Esteban Moro
Scientific Reports 3 1950 (2013)
PDF Journal Altmetric: 37

Talks:

Dynamics in Complex Networks: Analysing Real-world data my talk (video) at the Workshop on Complex Network Mining and Analysis. Transparencies can also be found here

Media:

Daily rhythms in mobile telephone communication

Tue, 13 Oct 2015 13:23:36 +0000

Authors:Talayeh Aledavood , Eduardo López, Sam G. B. Roberts, Felix Reed-Tsochas, Esteban Moro, Robin I. M. Dunbar, Jari Saramäki
Journal: PLoS ONE 10(9), e0138098 (2015) LINK

Abstract: Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further, questionnaire studies have identified important individual differences in circadian rhythms, with people broadly categorised into morning-like or evening-like individuals. However, little is known about the social aspects of these circadian rhythms, or how they vary across individuals. In this study we use a unique 18-month dataset that combines mobile phone calls and questionnaire data to examine individual differences in the daily rhythms of mobile phone activity. We demonstrate clear individual differences in daily patterns of phone calls, and show that these individual differences are persistent despite a high degree of turnover in the individuals’ social networks. Further, women’s calls were longer than men’s calls, especially during the evening and at night, and these calls were typically focused on a small number of emotionally intense relationships. These results demonstrate that individual differences in circadian rhythms are not just related to broad patterns of morningness and eveningness, but have a strong social component, in directing phone calls to specific individuals at specific times of day.

From Seconds to Months: multi-scale dynamics of mobile telephone calls

Thu, 07 May 2015 12:39:43 +0000

Authors:Jari Saramaki, Esteban Moro
Journal: Eur. Phys. J. B (2015) 88: 164 LINK | **arXiv

Abstract: Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and “zoom out” towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.