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Variation across Scales: Measurement Fidelity under Twitter Data Sampling [article]

Siqi Wu, Marian-Andrei Rizoiu, Lexing Xie
2020 arXiv   pre-print
By constructing complete tweet streams, we show that Twitter rate limit message is an accurate indicator for the volume of missing tweets. Sampling also differs significantly across timescales.  ...  For retweet cascades, we observe changes in distributions of tweet inter-arrival time and user influence, which will affect models that rely on these features.  ...  The collection period is from 2019-11-06 to 2019-11-19. The streaming client is a program that receives streaming data via Twitter API.  ... 
arXiv:2003.09557v3 fatcat:oyca3rugorby5isxld3djo4p5q

Tackling Climate Change with Machine Learning [article]

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli (+6 others)
2019 arXiv   pre-print
ML has been applied to monitor public sentiment about such bike shares via tweets [256] .  ...  Following seminal research on modeling pricing in markets as a bandit problem [776] , many works have applied bandit and other reinforcement learning (RL) algorithms to determine prices or other market  ... 
arXiv:1906.05433v2 fatcat:ykmqsivkbfcazaz3wl5f7srula

Measuring Collective Attention in Online Content: Sampling, Engagement, and Network Effects [article]

Siqi Wu, University, The Australian National
2021
Understanding how the content captures collective attention has become a challenge of growing importance.  ...  We find that the volume of missing tweets can be estimated by Twitter rate limit me [...]  ...  collected tweets with the complete set.  ... 
doi:10.25911/en55-sd26 fatcat:bkxvk4nbkfahflpqa2adycz7va

Human mobility: Models and applications

Hugo Barbosa, Marc Barthelemy, Gourab Ghoshal, Charlotte R. James, Maxime Lenormand, Thomas Louail, Ronaldo Menezes, José J. Ramasco, Filippo Simini, Marcello Tomasini
2018 Physics reports  
Recent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate  ...  This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems.  ...  Indeed, services such as Twitter, Facebook, Foursquare and Flickr collect geotagged data every time a user enables localization for the content being posted (e.g., checking-in at a restaurant with friends  ... 
doi:10.1016/j.physrep.2018.01.001 fatcat:4ewobqkarzho3dqjhd47iu3smu

Tackling climate change with machine learning [article]

David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj (+11 others)
2022
ML has been applied to monitor public sentiment about such bike shares via tweets [775] .  ...  ., via computer vision algorithms to parse satellite imagery).  ... 
doi:10.14279/depositonce-15739 fatcat:i3bxf2hmn5hcpfswamncwwdcla