An Ruopeng, Yang Yuyi, Batcheller Quinlan, Zhou Qianzi
Brown School, Washington University in St Louis, St Louis, Missouri.
J Public Health Manag Pract. 2023;29(5):633-639. doi: 10.1097/PHH.0000000000001721. Epub 2023 Feb 20.
As a primary source of added sugars, sugar-sweetened beverage (SSB) consumption may contribute to the obesity epidemic. A soda tax is an excise tax charged on selling SSBs to reduce consumption. Currently, 8 cities/counties in the United States have imposed soda taxes.
This study assessed people's sentiments toward soda taxes in the United States based on social media posts on Twitter.
We designed a search algorithm to systematically identify and collect soda tax-related tweets posted on Twitter. We built deep neural network models to classify tweets by sentiments.
Computer modeling.
Approximately 370 000 soda tax-related tweets posted on Twitter from January 1, 2015, to April 16, 2022.
Sentiment associated with a tweet.
Public attention paid to soda taxes, indicated by the number of tweets posted annually, peaked in 2016, but has declined considerably ever since. The decreasing prevalence of tweets quoting soda tax-related news without revealing sentiments coincided with the rapid increase in tweets expressing a neutral sentiment toward soda taxes. The prevalence of tweets expressing a negative sentiment rose steadily from 2015 to 2019 and then slightly leveled off, whereas that of tweets expressing a positive sentiment remained unchanged. Excluding news-quoting tweets, tweets with neutral, negative, and positive sentiments occupied roughly 56%, 29%, and 15%, respectively, during 2015-2022. The authors' total number of tweets posted, followers, and retweets predicted tweet sentiment. The finalized neural network model achieved an accuracy of 88% and an F1 score of 0.87 in predicting tweet sentiments in the test set.
Despite its potential to shape public opinion and catalyze social changes, social media remains an underutilized source of information to inform government decision making. Social media sentiment analysis may inform the design, implementation, and modification of soda tax policies to gain social support while minimizing confusion and misinterpretation.
作为添加糖的主要来源,饮用含糖饮料(SSB)可能会导致肥胖症的流行。汽水税是对销售含糖饮料征收的消费税,以减少消费。目前,美国有8个城市/县征收了汽水税。
本研究基于推特上的社交媒体帖子,评估了美国人对汽水税的看法。
我们设计了一种搜索算法,以系统地识别和收集推特上发布的与汽水税相关的推文。我们构建了深度神经网络模型,按情感对推文进行分类。
计算机建模。
2015年1月1日至2022年4月16日期间在推特上发布的约37万条与汽水税相关的推文。
与推文相关的情感。
每年发布的推文数量表明,公众对汽水税的关注度在2016年达到峰值,但此后大幅下降。引用与汽水税相关新闻但未表露情感的推文的流行率下降,与此同时,对汽水税表达中立情感的推文迅速增加。表达负面情感的推文的流行率从2015年到2019年稳步上升,然后略有平稳,而表达正面情感的推文的流行率保持不变。在2015 - 2022年期间,排除引用新闻的推文后,表达中立、负面和正面情感的推文分别约占56%、29%和15%。作者发布的推文总数、关注者和转发量可预测推文情感。最终的神经网络模型在预测测试集中的推文情感时,准确率达到88%,F1分数为0.87。
尽管社交媒体有塑造公众舆论和推动社会变革的潜力,但它仍然是政府决策中未得到充分利用的信息来源。社交媒体情感分析可为汽水税政策的设计、实施和修改提供参考,以获得社会支持,同时尽量减少困惑和误解。