Bir Twitter araştırması örneği
My QCRI colleagues Kiran Garimella and Ingmar Weber recently co-authored an important study on migration patterns discerned from Twitter. The study was co-authored with Bogdan State (Stanford) and lead author Emilio Zagheni (CUNY). The authors analyzed 500,000 Twitter users based in OECD countries between May 2011 and April 2013. Since Twitter users are not representative of the OECD population, the study uses a “difference-in-differences” approach to reduce selection bias when in out-migration rates for individual countries. The paper is available here and key insights & results are summarized below.
To better understand the demographic characteristics of the Twitter users under study, the authors used face recognition software (Face++) to estimate both the gender and age of users based on their profile pictures. “Face++ uses computer vision and data mining techniques applied to a large database of celebrities to generate estimates of age and sex of individuals from their…
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