Saura Jose Ramon, Reyes-Menendez Ana, Thomas Stephen B
Rey Juan Carlos University, Spain.
University of Maryland, United States of America.
Internet Interv. 2020 Mar 19;20:100312. doi: 10.1016/j.invent.2020.100312. eCollection 2020 Apr.
Using user-generated content (UGC) on Twitter, the present study identifies the main themes that revolve around the concept of healthy diet and determine user feelings about various foods. Using a dataset of tweets with the hashtag "#Diet" or "#FoodDiet" (n = 10.591), we first use a Latent Dirichlet Allocation (LDA) model to identify the food categories most discussed on Twitter. Then, based on the results of the LDA model, we apply sentiment analysis to divide the identified tweets into three groups (negative, positive and neutral) based on the feelings expressed in corresponding tweets. Finally, the text mining approach is performed to identify foods according to the feelings expressed about those in corresponding tweets, as well as to derive key indicators that collectively present the UGC-based knowledge of healthy eating. The results of the present study show that among the foods most negatively perceived in the UGC are bacon, sugar, processed foods, red meat, and snacks. By contrast, water, apples, salads, broccoli and spinach are evaluated more positively. Furthermore, our findings suggest that the collective UGC knowledge is lacking on such healthy foods as fish, poultry, dry beans, nuts, as well as yogurt and cheese. The results of the present study can help the World Health Organization (WHO), as well as other institutions concerned with the study of healthy eating, to improve their communication policies on healthy products and preparation of balanced diets.
本研究利用推特上的用户生成内容（UGC），确定了围绕健康饮食概念的主要主题，并判断了用户对各类食物的看法。我们使用一个带有“#Diet”或“#FoodDiet”标签的推文数据集（n = 10591），首先运用潜在狄利克雷分配（LDA）模型来识别推特上讨论最多的食物类别。然后，基于LDA模型的结果，我们应用情感分析，根据相应推文中表达的情感，将识别出的推文分为三组（负面、正面和中性）。最后，采用文本挖掘方法，根据相应推文中对食物表达的情感来识别食物，并得出关键指标，这些指标共同呈现了基于用户生成内容的健康饮食知识。本研究结果表明，在用户生成内容中负面评价最多的食物有培根、糖、加工食品、红肉和零食。相比之下，水、苹果、沙拉、西兰花和菠菜的评价更为正面。此外，我们的研究结果表明，对于鱼类、家禽、干豆、坚果以及酸奶和奶酪等健康食品，基于用户生成内容的知识较为匮乏。本研究结果可帮助世界卫生组织（WHO）以及其他关注健康饮食研究的机构改进其关于健康食品的传播政策和均衡饮食的制定。
