1. Are papers addressing certain diseases perceived where these diseases are prevalent? The proposal to use Twitter data as social-spatial sensors
- Author
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Vanash M. Patel, Robin Haunschild, and Lutz Bornmann
- Subjects
FOS: Computer and information sciences ,RNA viruses ,Bacterial Diseases ,Viral Diseases ,Biomedical Research ,Epidemiology ,Computer science ,Human immunodeficiency virus (HIV) ,Social Sciences ,HIV Infections ,Pathology and Laboratory Medicine ,medicine.disease_cause ,Geographical locations ,Medical Conditions ,Sociology ,Immunodeficiency Viruses ,Medicine and Health Sciences ,Prevalence ,Digital Libraries (cs.DL) ,Multidisciplinary ,Geography ,05 social sciences ,Social Communication ,Computer Science - Digital Libraries ,Research Assessment ,Infectious Diseases ,Social Networks ,Medical Microbiology ,Viral Pathogens ,Viruses ,Medicine ,Pathogens ,050904 information & library sciences ,Network Analysis ,Research Article ,Infectious agent ,Research evaluation ,Computer and Information Sciences ,General Science & Technology ,Science ,Twitter ,Internet privacy ,MEDLINE ,Research and Analysis Methods ,050905 science studies ,Microbiology ,World health ,Retroviruses ,Parasitic Diseases ,medicine ,Tuberculosis ,Humans ,Microbial Pathogens ,Tuberculosis, Pulmonary ,Spatial Analysis ,Altmetrics ,business.industry ,Lentivirus ,Organisms ,Biology and Life Sciences ,HIV ,Tropical Diseases ,Communications ,United States ,Influenza ,Malaria ,North America ,People and places ,0509 other social sciences ,business ,Social Media - Abstract
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 these 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 these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets.
- Published
- 2020