This article aims to contribute to the growing scholarship on the use of social media by humanitarian organisations in a crisis. Although social media’s role in times of crisis has been rigorously studied, much of this work looks at the distribution or collection of information by first-responders or relief organisations. However, there is a growing interest in the analysis of social media content to understand community perceptions and to guide public health and risk communication interventions.
It explores some key limitations of data collected using Social Media Analytics (SMA) tools in fairly representing community-wide perceptions. Through a review of ‘social listening reports’ produced by UN bodies and international aid organisations, this article will explore whether these data deficiencies are fairly represented.
A challenge impacting all analysis of social media data, either via AI or through manual collection, is the difficulty in determining the authenticity of the users who post.
The article concludes that while there are many well documented limitations in the use of social media discourse to holistically represent community perceptions, these limitations are not adequately discussed in the reporting produced from this data. Consequentially, users of this analysis cannot adequately weigh the quality of the data when using it to influence policy decisions.