When she posts next? A comparison of refresh strategies for Online Social Networks
Max-Emanuel Keller, Alexander Döschl, Peter Mandl, Alexander Schill · 2021
The synchronization of data against external sources with as few well-timed requests as possible is a challenge in several domains, that also applies to online social networks (OSNs). This paper examines algorithms that can be used to predict appropriate update intervals for feeds on Facebook and Twitter. The metrics to be optimized are the delay, meaning the time between publication and retrieval of the posts, as well as the requests per post. The approaches examined include static and adaptive algorithms as well as Poisson processes. The different strategies are first described, then applied to real-world data from Facebook and Twitter to finally compare and discuss the measurements. The various algorithms have different strengths and weaknesses. Hence, we show that with Poisson processes, the most fitting update intervals can be found, which keep both the post delay and the number of requests in a good ratio.