Sebastián Pinto
@SebaPinto88
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Becario Postdoctoral - DF - UBA
Buenos Aires, Argentina
Joined January 2015
RT @delpozosofia: Posiblemente coincidamos en que los usuarios con una ideología política bien definida tienden a compartir noticias compat….
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RT @delpozosofia: My last PhD project is out 🥹, I'm so grateful to the whole team! Politically labeled X users sharing news during election….
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RT @polbalen: In the last weeks, in @SoPhyLabDF @Fisica_UBA @Exactas_UBA have published three new papers addressing different aspects of e….
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RT @polbalen: 2 - “Analyzing User Ideologies and Shared News During the 2019 Argentinian Elections”, with @delpozosofia @SebaPinto88 @Elnon….
epjdatascience.springeropen.com
The extensive data generated on social media platforms allow us to gain insights over trending topics and public opinions. Additionally, it offers a window into user behavior, including their content...
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RT @KaczerLaura: Se buscan estudiantes de Cs. Biológicas para realizar la tesina en el proyecto de “Plasticidad de la memoria de palabras".….
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Finally, remember that Argentina not only has a Messiah, but also an Angel
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Our motivation with this paper is to show how a simple mathematical model can help to understand the mechanisms behind the emergence of collective social phenomena and provide metrics that can be directly measured from data.
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The model successfully fits the data and allows inferring a measure of social sensibility that correlates with human mobility data.
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This model was based on an early one proposed by Mark Granovetter which uses the concept of critical mass for understanding the aggregation process in riots.
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We proposed a simple mathematical model for the dynamics of public interest in terms of media coverage and social interactions, using the volume of tweets and retweets as a proxy of public interest, and the volume of news as a proxy of media coverage.
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We studied the mechanisms behind the evolution of public interest in events related to the Black Live Matters movement. Our research question was why in some cases people seem to be more engaged with certain topics than others despite the coverage given by mass media.
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Last days of 2022 and after the Football World Cup won by Argentina in Qatar, a new publication in @PhysRevE with @marc_trev, @polbalen, in @SoPhyLabDF from @Fisica_UBA.
journals.aps.org
We set up a simple mathematical model for the dynamics of public interest in terms of media coverage and social interactions. We test the model on a series of events related to violence in the US...
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Pase lo que pase, gracias por el primer tiempo más feliz de nuestras vidas. .
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RT @TomiChi3: ¿qué hacemos desde la intersección entre las ciencias sociales y las naturales para entender la proliferación de los discurso….
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RT @nex_ciencia: Investigadores de @Exactas_UBA analizaron el comportamiento de usuarios de Twitter -“políticamente activos” y “políticame….
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RT @delpozosofia: En Twitter compartimos noticias y vemos lo que otros comparten también. En este trabajo tomamos muestras de datos de este….
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RT @laura_astroph: Estudiando científicamente la polarización a.k.a "grieta" @polbalen en el DDF2022 @Fisica_UBA
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RT @labestiae: --GRAN SORTEO. La extraordinaria novela de McShane, 'Sesión en una tarde de lluvia'. --Solo con retwittear y seguir a La Be….
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RT @KaczerLaura: Nuevo experimento!! Es un juego muy divertido de preguntas, respuestas y asociaciones de palabras! Para cualquier edad, po….
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Our last preprint with @polbalen and @marc_trev in @SoPhyLabDF @Fisica_UBA. A little contribution to fill the gap between low-dimensional sociophysics-based models and social media data.
Reconstructing public engagement from social media content volume. (arXiv:2112.11644v1 [physics.soc-ph])
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