Simulating real-time Twitter data from historical datasets

Shane Halse, William Grace, Jess Kropczynski, Andrea Tapia

Research output: Contribution to conferencePaperpeer-review


In this paper, we will discuss a system design for simulating social media data based on historical datasets. While many datasets containing data collected from social media during crisis have become publicly available, there is a lack of tools or systems can present this data on the same timeline as it was originally posted. Through the design and use of the tool discussed in this paper, we show how historical datasets can be used for algorithm testing, such as those used in machine learning, to improve the quality of the data. In addition, the use of simulated data also has its benefits in training scenarios, which would allow participants to see real, non-fabricated social media messages in the same temporal manner as found on a social media platform.Lastly, we will discuss the positive reception and future improvements suggested by 911 Public Safety Answering Point (PSAP) professionals.
Original languageEnglish
StatePublished - May 19 2019


Dive into the research topics of 'Simulating real-time Twitter data from historical datasets'. Together they form a unique fingerprint.

Cite this