Real-time monitoring and analysis of vaccine concerns over time and location could help immunisation programmes to tailor more effective and timely strategies to address specific public health concerns. In recent years attempts [1, 2] are being made to develop a more systematic monitoring of broader public vaccine concerns resulting in vaccine refusals and potential disease outbreaks. Automated sentiment analysis software applications are being developed to detect and track the emergence and spread, geographically and temporally, of online social media reports on vaccines by developing a new application for opinion mining and sentiment analysis. Although many of the current approaches for automated sentiment analysis provide a timely method to assess the sentiment of a population towards vaccination, they do not assess beliefs, perceptions and behaviours. Incorporating semantic approach by using ontologies captures the domain knowledge and supports automated extraction and analysis of text in blog posts related to vaccination.
Objective
This paper presents our approach on design and development of an integrated semantic platform to capture the domain knowledge on vaccine sentiments, beliefs, and behaviours using ontologies. The vaccine sentiment ontology (VASON) provides more structure around the vast amount of unstructured data scattered over blog posts to facilitate blog content analysis, and discovering patterns of words or phrases in blogs text (e.g. specifying topics, themes, sentiment, beliefs and so on). It also assists in revealing opinionated claims and assertions in blogs and specifying the authors, forms, functions, geographical locations, audiences of blogs, as well as bloggers’ motives.