The Social Media Macroscope (SMM): A New Open Environment for Research using Social Media Data

  • The SMM is a science gateway to enable research using social media data without the need for programming skills.
  • All algorithms in the SMM are transparent in their methodology (non-black-box) and the SMM is FREE for academic and educational use.
  • All tools in the SMM are (and will be) open-source.
  • We believe that our environment will be extremely valuable even for commercial use, and our platform will be accessible at a far lower cost for commercial use than what is current out in the market.
  • You can immediately start using the SMM for academic and educational use; if you are a commercial entity, you can immediately test out the fully functioning system right now at www.socialmediamacroscope.org. If you are going to use it for commercial use after testing it out, please contact us at otm@illinois.edu.
For the researcher that is primarily focused on applying computational methods to answer an applied social research question, the SMM provides an easy to use interface (no programming required) with algorithms that are fully documented and non-black-box (tied to CS academic research papers).
For the researcher that is primarily focused on building computational algorithms, the SMM provides a landing place besides a GitHub in which social researchers can test the validity of the algorithm directly to their social research questions. The SMM also is building up connections as well as stores of social media data (in line with Terms of Services for each social media platform) to give computational researchers more data to build their algorithms against.
For researchers within industry companies (such as marketing/advertising professionals), the plethora of social media analytics platforms that have algorithms that are black box are not really helpful for providing confidence in the accuracy of their outputs. Additionally, those platforms are usually quite expensive to use. The SMM houses fully transparent algorithms and our initial goal is cost recovery for commercial use.
SMILE (Social Media Intelligence and Learning Environment) is kind of like your general all purpose social media analytics platform (akin to Radian6 and others), except ours is fully transparent in its methodologies.
BAE (Brand Analytics Environment) was our attempt to create a study (and a tool) in which we start looking at whether or not machine-learned personality detection via social media data actually affects behavior. We found a bit of evidence for this to be true and our study can be found at T&F or a free pre-print at ResearchGate.

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