Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. However, individual geo-located observations from social media are noisy and geographically inconsistent. Existing areas by which exposures are measured, like Zip codes, average over irrelevant administratively-defined boundaries. Hence, in order to enable studies of online social environmental measures like attitudes on social media and their possible relationship to health outcomes, first there is a need for a method to define the collective, underlying degree of social media attitudes by region. To address this, we create the Socio-spatial-Self organizing map, "SS-SOM" pipeline to best identify regions by their latent social attitude from Twitter posts. SS-SOMs use neural embedding for text-classification, and augment traditional SOMs to generate a controlled number of nonoverlapping, topologically-constrained and topically-similar clusters. We find that not only are SS-SOMs robust to missing data, the exposure of a cohort of men who are susceptible to multiple racism and homophobia-linked health outcomes, changes by up to 42% using SS-SOM measures as compared to using Zip code-based measures.
We have submitted your request - we will update you on status within the next 24 hours.
Sign up for further access to Scientific Publications and Authors!
What are PubFacts Points?
PubFacts points are rewards to PubFacts members, which allow you to better promote your profile and articles throughout PubFacts.com
How do I earn PubFacts Points?
Each member is given 50 PubFacts points upon signing up. You can earn additional points by completing 100% of your profile, creating and participating in discussions, and sharing other members research.
What can I do with PubFacts Points?
Currently, you can use PubFacts Points to promote and increase readership of your articles.