Ayora, VeruskaHorita, FlávioKamienski, Carlos2020-12-242020-12-242021-01-05978-0-9981331-4-0http://hdl.handle.net/10125/70955Online Social Networks (OSNs) have been increasingly used as a source of information for different applications, ranging from business, politics, and public services. However, there is a lack of information on the behavior of OSN platforms related to the completeness and agility of data that may impact big data processing and real-time services. In this paper, two of the most widely used social networks, Instagram and Twitter, are investigated to broaden the understanding of how the characteristics of each platform can influence the quality of data that can be collected. We performed a series of experiments to emulate data posting and collection automatically. Our results show that both platforms can deliver data with reasonably low latencies and high completeness, but Twitter can be up to eight times faster when it comes to multimedia messages.10 pagesEnglishAttribution-NonCommercial-NoDerivatives 4.0 InternationalDigital Methodsdigital methodsinstagramonline social networksplatform assessementtwitter10.24251/HICSS.2021.341