Piedrahita-Valdés Hilary, Piedrahita-Castillo Diego, Bermejo-Higuera Javier, Guillem-Saiz Patricia, Bermejo-Higuera Juan Ramón, Guillem-Saiz Javier, Sicilia-Montalvo Juan Antonio, Machío-Regidor Francisco
Department of Preventive Medicine and Public Health, Bromatology, Toxicology and Legal Medicine, University of Valencia, 46010 Valencia, Spain.
Faculty of Engineering and Technology, International University of La Rioja, 26006 Logroño, Spain.
Vaccines (Basel). 2021 Jan 7;9(1):28. doi: 10.3390/vaccines9010028.
Vaccine hesitancy was one of the ten major threats to global health in 2019, according to the World Health Organisation. Nowadays, social media has an important role in the spread of information, misinformation, and disinformation about vaccines. Monitoring vaccine-related conversations on social media could help us to identify the factors that contribute to vaccine confidence in each historical period and geographical area. We used a hybrid approach to perform an opinion-mining analysis on 1,499,227 vaccine-related tweets published on Twitter from 1st June 2011 to 30th April 2019. Our algorithm classified 69.36% of the tweets as neutral, 21.78% as positive, and 8.86% as negative. The percentage of neutral tweets showed a decreasing tendency, while the proportion of positive and negative tweets increased over time. Peaks in positive tweets were observed every April. The proportion of positive tweets was significantly higher in the middle of the week and decreased during weekends. Negative tweets followed the opposite pattern. Among users with ≥2 tweets, 91.83% had a homogeneous polarised discourse. Positive tweets were more prevalent in Switzerland (71.43%). Negative tweets were most common in the Netherlands (15.53%), Canada (11.32%), Japan (10.74%), and the United States (10.49%). Opinion mining is potentially useful to monitor online vaccine-related concerns and adapt vaccine promotion strategies accordingly.
根据世界卫生组织的说法,疫苗犹豫是2019年全球健康面临的十大主要威胁之一。如今,社交媒体在有关疫苗的信息、错误信息和虚假信息传播中发挥着重要作用。监测社交媒体上与疫苗相关的对话可以帮助我们确定在每个历史时期和地理区域中有助于增强疫苗信心的因素。我们采用了一种混合方法,对2011年6月1日至2019年4月30日在推特上发布的1,499,227条与疫苗相关的推文进行了观点挖掘分析。我们的算法将69.36%的推文分类为中性,21.78%为正面,8.86%为负面。中性推文的比例呈下降趋势,而正面和负面推文的比例则随着时间的推移而增加。每年4月都会出现正面推文的峰值。正面推文的比例在一周的中间时段显著更高,在周末则下降。负面推文呈现相反的模式。在发布了≥2条推文的用户中,91.83%的人有同质化的两极化言论。正面推文在瑞士更为普遍(71.43%)。负面推文在荷兰(15.53%)、加拿大(11.32%)、日本(10.74%)和美国(10.49%)最为常见。观点挖掘对于监测在线疫苗相关问题并相应调整疫苗推广策略可能是有用的。