  We propose to use Twitter data as social-spatial sensors. This study deals
with the question whether research papers on certain diseases are perceived by
people in regions (worldwide) that are especially concerned by the diseases.
Since (some) Twitter data contain location information, it is possible to
spatially map the activity of Twitter users referring to certain papers (e.g.,
dealing with tuberculosis). The resulting maps reveal whether heavy activity on
Twitter is correlated with large numbers of people having certain diseases. In
this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and
malaria, since the World Health Organization ranks these diseases as the top
three causes of death worldwide by a single infectious agent. The results of
the social-spatial Twitter maps (and additionally performed regression models)
reveal the usefulness of the proposed sensor approach. One receives an
impression of how research papers on the diseases have been perceived by people
in regions that are especially concerned by the diseases. Our study
demonstrates a promising approach for using Twitter data for research
evaluation purposes beyond simple counting of tweets.
