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Table 4 Utility and challenges of social media listening

From: Utility of social media and crowd-intelligence data for pharmacovigilance: a scoping review

Utility and challenges of social media listening Count (%)
Utility of social media listening for pharmacovigilance
 Supplemental data to traditional post-marketing safety surveillance 31 (44.3%)
 Captures perceptions and consequences of treatment and adverse events 14 (20.0%)
 Large publicly available data source 14 (20.0%)
 Able to discover undocumented or rare adverse events 11 (15.7%)
 Promising early warning system 10 (14.3%)
 Computationally efficient 7 (10.0%)
 Captures prescription drug misuse/abuse 4 (5.7%)
 Not biased towards severe adverse events 7 (10.0%)
 Captures large geographical area 3 (4.3%)
 Useful for risk communication 3 (4.3%)
 Able to extract complex medical concepts 2 (2.9%)
 Can be more accurate than spontaneous reporting systems 2 (2.9%)
 Hypothesis-generating 2 (2.9%)
 Able to identify undocumented drug interactions 2 (2.9%)
 Findings are similar to traditional systems 1 (1.4%)
 Captures information on adherence related to adverse events 1 (1.4%)
Challenges of social media listening for pharmacovigilance
 Non-standard reporting format (informal language, format used to report information, amount of information provided by each user) 30 (42.9%)
 Difficult to draw complex semantic relationships from unstructured texts 14 (20.0%)
 May not be a representative population 13 (18.6%)
 Noise may exist in signal detection 12 (17.1%)
 Inadequate information to draw causality 9 (12.9%)
 Lacks comprehensive medical and demographic information 8 (11.4%)
 Subjective, incomplete or misinformation 6 (8.6%)
 Not a balanced coverage of all drugs and medical conditions 5 (7.1%)
 Data acquisition challenges due to host site restrictions 4 (5.7%)
 Duplication of data (double-counting) 4 (5.7%)
 Processing multi-lingual texts 3 (4.3%)
 Resource-intensive to process big data 2 (2.9%)