Division of Software, Yonsei University, Wonju, Gangwon-do, Republic of Korea.
Department of Nursing, Wonju College of Medicine, Yonsei University, Wonju, Gangwon-do, Republic of Korea.
PLoS One. 2022 Aug 25;17(8):e0273570. doi: 10.1371/journal.pone.0273570. eCollection 2022.
Adolescents are increasingly interested in weight control; hence, proper health education is important for helping them control their weight properly. This study was designed to pick out social media words that express adolescents' diet behaviors, and identify the associations and types between such words and the behaviors. It used text-mining techniques and semantic network analysis for related big data collected from the Internet on adolescents' diet behaviors. Text mining was used to extract meaningful information from unstructured text data, whereas semantic network analysis was used to understand the relationships between keywords. The top five keywords were "obesity," "health," "exercise," "eat," and "increase" in online news, and "exercise," "eat," "weight loss," "obesity," and "health" in blogs. The betweenness centrality of "appearance" was particularly higher than that of other centralities in online news. As a result of the CONCOR analysis, eight clusters each were identified in online news and blogs. This study's results will serve as a basis for weight management-related intervention strategies, reflecting the perspectives of adolescents. It also has significance as basic data to provide correct information, and establish desirable weight control in the future.
青少年越来越关注体重控制，因此，适当的健康教育对于帮助他们正确控制体重非常重要。本研究旨在挑选出表达青少年饮食行为的社交媒体词汇，并确定这些词汇与行为之间的关联和类型。它使用文本挖掘技术和语义网络分析，从互联网上收集关于青少年饮食行为的相关大数据。文本挖掘用于从非结构化文本数据中提取有意义的信息，而语义网络分析用于理解关键词之间的关系。网络新闻中排名前五的关键词是“肥胖”、“健康”、“锻炼”、“吃”和“增加”，博客中则是“锻炼”、“吃”、“减肥”、“肥胖”和“健康”。“外貌”的中介中心度明显高于网络新闻中其他中心度。通过 CONCOR 分析，在线新闻和博客中分别确定了八个簇。本研究结果将为体重管理相关干预策略提供依据，反映青少年的观点。作为提供正确信息和建立未来理想体重控制的基础数据，它也具有重要意义。
