Is the Sample Good Enough? Comparing Data from Twitters Streaming API with Twitters Firehose

Twitter is a social media giant famous for the exchange of short, 140-character messages called “tweets”. In the scientific community, the microblogging site is known for openness in sharing its data. It provides a glance into its millions of users and billions of tweets through a “Streaming API ” which provides a sample of all tweets matching some parameters preset by the API user. The API service has been used by many researchers, compa-nies, and governmental institutions that want to extract knowledge in accordance with a diverse array of ques-tions pertaining to social media. The essential drawback of the Twitter API is the lack of documentation concern-ing what and how much data users get. This leads re-searchers to question whether the sampled data is a valid representation of the overall activity on Twitter. In this work we embark on answering this question by compar-ing data collected using Twitter’s sampled API service with data collected using the full, albeit costly, Firehose stream that includes every single published tweet. We compare both datasets using common statistical metrics as well as metrics that allow us to compare topics, net-works, and locations of tweets. The results of our work will help researchers and practitioners understand the implications of using the Streaming API