People use social media to share their own opinions, including their feelings regarding health issues. The study reports the findings of an opinion mining analysis on immunisation conducted on Twitter in Italy from September 2016 to August 2017. Using supervised machine-learning algorithms, vaccine-related tweets were automatically categorised as opposed, in favour, or neutral in relation to the vaccination subject. During this time, the study saw an increase in the amount of tweets about this issue. According to the total study by category, 60% of tweets were classed as neutral, 23% were anti-vaccination, and 17% were pro-vaccination.
Vaccine-related events proved to be able to impact the amount and polarity of tweets. In particular, the adoption of the decree requiring obligatory immunisation for certain children’s illnesses had a significant impact on the social conversation in terms of the number of tweets. Attitude mining analysis based on Twitter proved to be a potentially valuable and timely sentinel system for assessing public opinion toward vaccination and, in the future, it may successfully help to the creation of suitable communication and information strategies.
Reference: https://www.tandfonline.com/doi/full/10.1080/21645515.2020.1714311
