Introduction: Social media listening and monitoring of user-generated content (UGC) in commercial marketing is central to measuring social media users' perceptions of a brand or company. Applications of social media analytics (SMA) have become common practice in marketing and are employed to predict consumer behavior. However, critical reflections on SMA applications to nonprofit marketing are lacking, despite the increased usage of SMA by nonprofit organizations. Objective: The article proposes to apply SMA to analyze UGC and identify how computational methodologies can help bolster strategic communication for nonprofit organizations and drive marketing strategy. Methodology: The article presents results from a 2-year (October 2017-January 2020) social media monitoring of the hashtag #DownSyndrome on Twitter and Instagram. SMA tools will be used. Specifically, sentiment analysis and topic modeling are employed to analyze tweets and Instagram posts, while image classification is used to analyze Instagram images. Findings: The results highlight a strong stereotypical characterization of people with Down syndrome in content that is generated by social media users and identify possibilities and challenges ahead of nonprofit organizations pushing specific agendas. Originality and Contribution: This study is the first to offer a review of SMA, apply them to a nonprofit context and reflect on aspects of representation and stereotypization through them. It ultimately proposes to support nonprofit and voluntary marketing research and practice by integrating UGC research and computational techniques into the broader discussion of ethical content strategy in social media nonprofit marketing.