Unconventional physical activity promotion : exploring the effectiveness of DDP yoga through sentiment analysis on Twitter

Abstract

The worrying trend of physical inactivity has prompted the development of online social network interventions that promote physical activity (PA). However, a good understanding of online communications is essential for effective PA interventions online. With the increasing popularity of online social networks, unstructured text data within these platforms present a great opportunity to examine public opinions and discussions. While studies have examined these data on PA and public health, they have not considered observing a specific fitness regime or programme that could provide a deeper understanding of PA-related conversations. This study explored the use of natural language processing concepts in the field of big data analytics to observe Twitter conversations regarding an unconventional fitness movement developed by Diamond Dallas Page (DDP), known as DDP Yoga (DDPY). Tweets that mentioned DDPY were collected, and 13,069 tweets from 4,343 unique users were analysed through topic modelling and sentiment analysis. Results indicated particularly positive sentiments among Twitter users and many tweets were focused on providing support and encouragement for the DDPY community. DDPY appeared to be successful in utilizing the viral aspects of social media to reinforce positive messages promoting PA and build a cohesive fitness community online. The findings may be relevant for future studies on PA interventions using online social networks or current PA promoting efforts in public or private organisations. The current age of digitisation affords the use of data analytics to gain useful insights within online social networks and improve interventions that address tough issues such as physical inactivity.