Lidia Flores1, Sean D Young1,2. 1. Department of Emergency Medicine, University of California, Irvine, CA, USA. 2. University of California Institute for Prediction Technology, Department of Informatics, Bren School of Information and Computer Sciences, UC Irvine, Irvine, CA, USA.
Abstract
BACKGROUND: New data sources and analysis methods are urgently needed to improve opioid surveillance and prevent potential overdose. Social media data is one potential data source that might be used and integrated to address this issue. Objective: This study explored opioid-related topics discussed across geographical regions of varying population sizes to determine whether social media data might inform opioid surveillance. Methods: Between March 17th to July 17th, 2020, we collected tweets (N = 19,721) mentioning opioid-related keywords across seven cities within the United States. Results: Results found that opioid-related keywords were distributed as follows: New York (29%), Los Angeles (23%), Chicago (18%), Atlanta (18%), San Francisco (8%), Iowa (3%), and Orange County, CA (1%). We also found regional differences in the types of opioids and topics mentioned. Conclusions: Findings suggest the feasibility of using opioid-related social media data to inform surveillance efforts, as well as potential regional and time-varying differences in topics discussed.
BACKGROUND: New data sources and analysis methods are urgently needed to improve opioid surveillance and prevent potential overdose. Social media data is one potential data source that might be used and integrated to address this issue. Objective: This study explored opioid-related topics discussed across geographical regions of varying population sizes to determine whether social media data might inform opioid surveillance. Methods: Between March 17th to July 17th, 2020, we collected tweets (N = 19,721) mentioning opioid-related keywords across seven cities within the United States. Results: Results found that opioid-related keywords were distributed as follows: New York (29%), Los Angeles (23%), Chicago (18%), Atlanta (18%), San Francisco (8%), Iowa (3%), and Orange County, CA (1%). We also found regional differences in the types of opioids and topics mentioned. Conclusions: Findings suggest the feasibility of using opioid-related social media data to inform surveillance efforts, as well as potential regional and time-varying differences in topics discussed.
Entities:
Keywords:
Real-time data; Twitter data; drug consumption; geographical locations; opioids; public health surveillance
Authors: Gabriel J Milinovich; Simon M R Avril; Archie C A Clements; John S Brownstein; Shilu Tong; Wenbiao Hu Journal: BMC Infect Dis Date: 2014-12-31 Impact factor: 3.090