Twitter

Temporal, structural and activity patterns in social networks are related to human behavior. Thus, networks do have different shape and dynamics under different exogenous and endogenous shocks or conditions. In the last years we have addressed the question of whether we can use our understanding of social networks to anticipate, predict or measure important phenomena as information propagation, disaster damage, unemployment shocks, weather conditions, gender digital divide, etc. For example in a series of papers, we demonstrated for the first time the ability of the so-called “friendship paradox” in social networks to get better collection of users (sensors) that can anticipate meme, news or event-related information propagation in networks. ...

I started using Twitter more than 10 years ago (!). I open an account in this social network in 2008 and although I was not using it too much for the first year, I become a frequent user after that. It has helped me to get news, information both for my personal and professional interests. But not only that, Twitter has been also the data source for our research, that helped us to investigate the relationship between human behavior in the social platform and paramount problems in our society as information propagation, unemployment, disaster damage, political opinion. ...

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. ...

Nice article (in Spanish) in Yorokobu magazine about the use of Twitter in science, highlighting our work on the use of social media for rapid assessment of natural disaster management El romance entre Twitter y la ciencia «Twitter y las otras redes sociales están entre los más grandes archivos de actividad humana existentes y, al contrario que con las encuestas, ahora tenemos la posibilidad de analizar millones de mensajes, opiniones e interacciones de personas en diferentes contextos como la política, economía o el ocio», explica el matemático Esteban Moro, investigador en la Carlos III de Madrid. ...

Authors: Yury Kryvasheyeu1, Haohui Chen, Nick Obradovich, Esteban Moro, Pascal Van Hentenryck, James Fowler and Manuel Cebrian Journal: Science Advances 11 Mar 2016: Vol. 2, no. 3, e1500779 (2016) LINK Abstract: Could social media data aid in disaster response and damage assessment? Countries face both an increasing frequency and an increasing intensity of natural disasters resulting from climate change. During such events, citizens turn to social media platforms for disaster-related communication and information. ...

Authors:Alejandro Llorente, Manuel García-Herránz, Manuel Cebrián and Esteban Moro Journal: PLoS ONE 10(5): e0128692 (2014) LINK Summary: Publicly available social media data can be used to quantify deviations from typical patterns of behavior and uncover how these deviations signal the socio-economical status of regions. Using data from geolocalized Twitter messages, we find that unemployment is correlated with technology adoption, daily activity, diversity in mobility patterns and correctness in communication style. These behavioral metrics serve to build simple, interpretable, and cost-effective socio-economical predictors from these novel digital datasets. ...