Public sense of dental implants on social media: A cross-sectional study based on text analysis of comments

感觉 情绪分析 多学科方法 社会化媒体 心理学 主题(计算) 内容分析 舆论 牙科 医学 社会心理学 计算机科学 社会学 社会科学 政治学 政治 机器学习 万维网 操作系统 法学
作者
Shaoping Ma,Chenhao Bai,Chunchun Chen,Jingyao Bai,Mengfei Yu,Yi Zhou
出处
期刊:Journal of Dentistry [Elsevier]
卷期号:137: 104671-104671
标识
DOI:10.1016/j.jdent.2023.104671
摘要

To investigate the most discussed topics and possible new interests in dental implants among the public, as well as the public sentiments toward dental implants through topic and sentiment analysis of online comments. Comments of the top 100 most viewed dental implant-related YouTube videos were studied. The comments were analyzed by topic analysis (LDA topic model, Word co-occurrence analysis) and sentiment analysis. The basic information of videos was collected and classified. Video quality was evaluated by GQS criteria and 9-point usefulness scoring system. Statistical analyses were performed using Kruskal-Wallis test, Mann-Whitney U-tests, and Spearman correlation analysis. 74 videos with 61,618 comments were considered eligible in this study. Most videos targeted the public with high viewing and comments, but the theme was single and the quality was low. From topic analysis, the most discussed topics in the comments were procedure, cost, feelings associated with prognosis, and expectations. Multidisciplinary approaches in implant dentistry were frequently discussed. From sentiment analysis, the public mainly expressed positive sentiment through comments. In detail, the public had positive feelings about aesthetics and health, negative feelings about pain, and neutral feelings about cost. The hot topics of public concern were procedure, cost, feelings associated with prognosis, and expectations. Intriguingly, multidisciplinary approaches in implant dentistry have emerged as a new hot subtopic within the topic “procedure”. Based on the sentiment analysis of the comments, the general sentiment expressed by the public toward dental implants was predominantly positive. Text mining can extract data from social media to explore public interest in dentistry. Clinicians should convey reasonable expectations and understanding about dental implants, especially addressing the most public-concerned topics (procedure, cost, feelings, and expectations), and provide patients with well-grounded multidisciplinary treatment plans to meet the growing public demand.
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