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Network theory and computational social science allow us to understand collective human behaviour by analysing data and making models of the digital interactions we have online. The closing gap between off- and online activities lets us perform this task better than ever, bringing both knowledge of the large-scale structure of society, and challenges in predicting the future behaviour of individuals. Here are some of my research lines in this amazing field

Complex contagion on techno-social networks

We use large-scale data from online social platforms to study and predict the temporal evolution of social contagion processes and cascading behaviour related to the use of innovations and new digital markets. By considering data features like weighted or multiplex social interactions, product competition,
and temporal social networks, we aim at increasing the explanatory and predictability power of social contagion models

  • G. Iñiguez, Z. Ruan, K. Kaski, J. Kertész, M. Karsai, Service adoption spreading in online social networks. In S. Lehmann and Y.-Y. Ahn, eds., Spreading Dynamics in Social Systems (Springer Nature, 2018). DOI: 10.1007/978-3-319-77332-2. arXiv: 1706.09777.
  • S. Unicomb, G. Iñiguez, M. Karsai, Threshold driven contagion on weighted networks. Scientific Reports 8, 3094 (2018). DOI: 10.1038/s41598-018-21261-9. arXiv: 1707.02185
  • M. Karsai, G. Iñiguez, R. Kikas, K. Kaski, J. Kertész. Local cascades induced global contagion: How heterogeneous thresholds, exogenous effects, and unconcerned behaviour govern online adoption spreading. Scientific Reports 6, 27178 (2016). DOI: 10.1038/srep27178. arXiv: 1601.07995
  • Z. Ruan, G. Iñiguez, M. Karsai, J. Kertész. Kinetics of social contagion. Physical Review Letters 115, 218702 (2015). DOI: 10.1103/PhysRevLett.115.218702. arXiv: 1506.00251
  • M. Karsai, G. Iñiguez, K. Kaski, J. Kertész. Complex contagion process in spreading of online innovation. Journal of the Royal Society Interface 11, 20140694 (2014). DOI: 10.1098/rsif.2014.0694arXiv: 1405.6879

Conflict emergence and resolution in Wikipedia

We validate opinion-formation models with data to emulate the
temporal evolution of conflicts between editors in Wikipedia. We find three typical scenarios for the way editors disagree while writing articles: short conflicts, plateaus of consensus among fights, and uninterrupted controversy. We wish not only to identify the ways by which people manage to collaborate despite their differences, but to propose efficient measures of prevention and control to minimise the harmful effects of social conflict

  • G. Iñiguez, J. Török, T. Yasseri, K. Kaski, J. Kertész. Modeling social dynamics in a collaborative environment. EPJ Data Science 3, 7 (2014). DOI: 10.1140/epjds/s13688-014-0007-z. arXiv: 1403.3568
  • G. Iñiguez, Statistical Physics of Opinion and Social Conflict (Aalto University publication series, Helsinki, 2013). ISBN: 978-952-60-5108-6
  • J. Török, G. Iñiguez, T. Yasseri, M. San Miguel, K. Kaski, J. Kertész. Opinions, conflicts, and consensus: Modeling social dynamics in a collaborative environment. Physical Review Letters 110, 088701 (2013). DOI: 10.1103/PhysRevLett.110.088701. arXiv: 1207.4914

Opinion formation and deception on coevolving social networks

Opinions synthesize our perceptions and the knowledge we have of the external world, other people, and ourselves. To better understand the impact opinions have on social interactions and decision-making, we perform small controlled experiments and analyse idealized models of opinion formation, deception, and network change, letting us gauge how opinions influence the structure and dynamics of society

  • R. A. Barrio, T. Govezensky, R. Dunbar, G. Iñiguez, K. Kaski. Dynamics of deceptive interactions in social networks. Journal of the Royal Society Interface 12, 20150798 (2015). DOI: 10.1098/rsif.2015.0798. arXiv: 1509.03918
  • G. Iñiguez, T. Govezensky, R. Dunbar, K. Kaski, R. A. Barrio. Effects of deception in social networks. Proceedings of the Royal Society B 281, 20141195 (2014). DOI: 10.1098/rspb.2014.1195. arXiv: 1406.0673
  • G. Iñiguez, Statistical Physics of Opinion and Social Conflict (Aalto University publication series, Helsinki, 2013). ISBN: 978-952-60-5108-6
  • G. Iñiguez, J. Tagüeña-Martínez, K. Kaski, R. A. Barrio. Are opinions based on science: Modelling social response to scientific facts. PLoS ONE 7, e42122 (2012). DOI: 10.1371/journal.pone.0042122. arXiv: 1109.1488
  • G. Iñiguez, J. Kertész, K. Kaski, R. A. Barrio. Phase change in an opinion-dynamics model with separation of time scales. Physical Review E 83, 016111 (2011). DOI: 10.1103/PhysRevE.83.016111. arXiv: 1009.2643
  • G. Iñiguez, R. A. Barrio, J. Kertész, K. Kaski. Modelling opinion formation driven communities in social networks. Computer Physics Communications 182, 1866–1869 (2011). DOI: 10.1016/j.cpc.2010.11.020. arXiv: 1007.4177
  • G. Iñiguez, J. Kertész, K. Kaski, R. A. Barrio. Opinion and community formation in coevolving networks. Physical Review E 80, 066119 (2009). DOI: 10.1103/PhysRevE.80.066119. arXiv: 0908.1068v2

Generic features of rank dynamics in complex systems

Many complex systems develop hierarchies of their elements that emerge from networked interactions. These hierarchies evolve according to system-dependent mechanisms of interaction and reflect the relevance of elements in performing a function in the system. By analysing ranking data on languages and sports, as well as simple models of rank dynamics, we show there are generic features of hierarchy stability that allow us to model and predict patterns of hierarchical behaviour across complex systems

  • J. E. Snellman, G. Iñiguez, J. Kertész, R. A. Barrio, K. Kaski. Status maximization as a source of fairness in a networked dictator game. Journal of Complex Networks cny022 (2018). DOI: 10.1093/comnet/cny022. arXiv: 1806.05542
  • J. A. Morales, E. Colman, S. Sánchez, F. Sánchez-Puig, C. Pineda, G. Iñiguez, G. Cocho, J. Flores, C. Gershenson. Rank dynamics of word usage at multiple scales. Frontiers in Physics 6, 45 (2018). DOI: 10.3389/fphy.2018.00045. arXiv: 1802.07258
  • S. Sánchez, G. Cocho, J. Flores, C. Gershenson, G. Iñiguez, C. Pineda. Trajectory stability in the traveling salesman problem. Complexity 2018, 2826082 (2018). DOI: 10.1155/2018/2826082. arXiv: 1708.06945
  • J. E. Snellman, G. Iñiguez, T. Govezensky, R. A. Barrio, K. Kaski. Modelling community formation driven by the status of individual in a society. Journal of Complex Networks 5, 6, 817–838 (2017). DOI: 10.1093/comnet/cnx009. arXiv: 1702.02541
  • J. A. Morales, S. Sánchez, J. Flores, C. Pineda, C. Gershenson, G. Cocho, J. Zizumbo, R. F. Rodríguez, G. Iñiguez. Generic temporal features of performance rankings in sports and games. EPJ Data Science 5, 33 (2016). DOI: 10.1140/epjds/s13688-016-0096-y. arXiv: 1606.04153

contact me

iniguezg [AT] ceu [DOT] edu

DNDS, CEU, Budapest