#Twitter #Human Behavior

Twitter Session Analytics: Profiling Users’ Short-Term Behavioral Changes

Authors: Farshad Kooti, Esteban Moro, and Kristina Lerman Journal: Proceedings of SocInfo 2016 LINK Abstract: Human behavior shows strong daily, weekly, and monthly patterns. In this work, we demonstrate online behavioral changes that occur on a much smaller time scale: minutes, rather than days or weeks. Specifically, we study how people distribute their effort over different tasks during periods of activity on the Twitter social platform. We demonstrate that later in a session on Twitter, people prefer to per- form simpler tasks, such as replying and retweeting others’ posts, rather than composing original messages, and they also tend to post shorter messages. ...

#stock market #Human behavior #Big Data

Financial markets as empirical labs to study the evolving ecology of human decision making

Human decision making strategies evolve through time based on past experience and they are influence by the spectrum of other strategies with which they come into contact. Financial markets provide the best empirical lab to understand how human decide under risk and uncertainty. They are complex systems which provide massive datasets of detail records of human decisions which constantly evolve and collide in centralized or social structures. Furthermore financial markets provide us with a very simple measure of performance (profits, ROI), thus enabling us to study the relationship between human decision making strategies and performance. ...

#Human behavior #Credit Card Data #Predictability

The predictability of consumer visitation patterns

Authors: Coco Krumme, Alejandro Llorente, Manuel Cebrian, Alex (“Sandy”) Pentland & Esteban Moro Journal: Sci. Rep. 3, 1645; (2013). LINK Abstract: We consider hundreds of thousands of individual economic transactions to ask: how predictable are consumers in their merchant visitation patterns? Our results suggest that, in the long-run, much of our seemingly elective activity is actually highly predictable. Notwithstanding a wide range of individual preferences, shoppers share regularities in how they visit merchant locations over time. ...

#Temporal networks #Human behavior #Mobile Phone Data

Limited communication capacity unveils strategies for human interaction

Authors: Giovanna Miritello, Rubén Lara, Manuel Cebrián and Esteban Moro Journal: Scientific Reports 3, 1950 (2013). LINK Abstract: Social connectivity is the key process that characterizes the structural properties of social networks and in turn processes such as navigation, influence or information diffusion. Since time, attention and cognition are inelastic resources, humans should have a predefined strategy to manage their social interactions over time. However, the limited observational length of existing human interaction datasets, together with the bursty nature of dyadic communications have hampered the observation of tie dynamics in social networks. ...

#Social Networks #Human Behavior #Strategies

Time as a limited resource: Communication Strategy in Mobile Phone Networks

Authors: Giovanna Miritello, Esteban Moro, Rubén Lara, Rocío Martínez-López, Sam G. B. Roberts, Robin I. M. Dunbar Journal: Social Networks 35, 89 (2013) LINK | arXiv Abstract: We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tiestrength and the way in which users distributed their limited time across their network (disparity). ...

#Social Networks #Mobile Phone Data #Diffusion #Human behavior

Dynamical strength of social ties in information spreading

Authors: Giovanna Miritello, Esteban Moro y Rubén Lara Journal: Physical Review E (Rapid Comm) 83, 045102 (2011). LINK | arXiv Abstract: We investigate the temporal patterns of human communication and its influence on the spreading of information in social networks. The analysis of mobile phone calls of 20 million people in one country shows that human communication is bursty and happens in group conversations. These features have opposite effects in information reach: while bursts hinder propagation at large scales, conversations favor local rapid cascades. ...