Impact of Image Content on Medical Crowdfunding Success: A Machine Learning Approach

J Med Internet Res. 2024 Nov 15:26:e58617. doi: 10.2196/58617.

Abstract

Background: As crowdfunding sites proliferate, visual content often serves as the initial bridge connecting a project to its potential backers, underscoring the importance of image selection in effectively engaging an audience.

Objective: This paper aims to explore the relationship between images and crowdfunding success in cancer-related crowdfunding projects.

Methods: We used the Alibaba Cloud platform to detect individual features in images. In addition, we used the Recognize Anything Model to label images and obtain content tags. Furthermore, the discourse atomic topic model was used to generate image topics. After obtaining the image features and image content topics, we built regression models to investigate the factors that influence the results of crowdfunding success.

Results: Images with a higher proportion of young people (β=0.0753; P<.001), a larger number of people (β=0.00822; P<.001), and a larger proportion of smiling faces (β=0.0446; P<.001) had a higher success rate. Image content related to good things and patient health also contributed to crowdfunding success (β=0.082, P<.001; and β=0.036, P<.001, respectively). In addition, the interaction between image topics and image characteristics had a significant effect on the final fundraising outcome. For example, when smiling faces are considered in conjunction with the image topics, using more smiling faces in the rest and play theme increased the amount of money raised (β=0.0152; P<.001). We also examined causality through a counterfactual analysis, which confirmed the influence of the variables on crowdfunding success, consistent with the results of our regression models.

Conclusions: In the realm of web-based medical crowdfunding, the importance of uploaded images cannot be overstated. Image characteristics, including the number of people depicted and the presence of youth, significantly improve fundraising results. In addition, the thematic choice of images in cancer crowdfunding efforts has a profound impact. Images that evoke beauty and resonate with health issues are more likely to result in increased donations. However, it is critical to recognize that reinforcing character traits in images of different themes has different effects on the success of crowdfunding campaigns.

Keywords: crowdfunding success; image content; machine learning; medical crowdfunding; visual analytics.