Exploring the potential of online social listening for noncommunicable disease monitoring.

Abstract

Noncommunicable diseases (NCDs) are a significant global health challenge, claiming about 41 million lives annually. Early establishment of healthy habits is vital as childhood behaviors often persist into adulthood, affecting long-term well-being. However, pervasive health misinformation on social media exacerbates the challenge of addressing NCDs. The vast online information exposes individuals to misinformation, leading to uninformed health decisions. Countering this misinformation is crucial to promote accurate understanding and preventive strategies for NCDs, improving public health outcomes. To address this, the study proposes a system using online social listening (OSL) to collect and analyze social media data, focusing on children's nutrition, physical exercise, sleep patterns, and related NCD risk factors. This platform aids healthcare professionals in recognizing and responding to online misinformation, facilitating informed decision-making. Collaboration with parents, teachers, and healthcare providers aims to instill healthy habits in children from an early age. Utilizing the Twitter Application Programming Interface (API), the study collected data on NCDs, their risk factors, and their impact on children. Despite challenges from recent Twitter API policy changes, the methodology remains adaptable. Additionally, the study integrates diverse data sources, including traditional news outlets like PressReader, providing comprehensive coverage of health issues. Analysis comparing data from PressReader and Twitter underscores differences in discussion frequency and nature, emphasizing the need to leverage insights from various sources. The results highlight the effectiveness of the OSL system in identifying prevalent health topics, benefiting healthcare professionals. This collaborative approach positions the system as a valuable tool for addressing NCDs and promoting well-being. The study lays a foundation for future research, suggesting expansions to include additional platforms and languages, as well as advanced features like sentiment analysis.