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Can Twitter Be a Source of Information on Allergy? Correlation of Pollen Counts with Tweets Reporting Symptoms of Allergic Rhinoconjunctivitis and Names of Antihistamine Drugs

机译:Twitter可以成为过敏信息的来源吗?花粉计数与报告过敏性鼻结膜炎症状和抗组胺药名称的推文的相关性

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摘要

Pollen forecasts are in use everywhere to inform therapeutic decisions for patients with allergic rhinoconjunctivitis (ARC). We exploited data derived from Twitter in order to identify tweets reporting a combination of symptoms consistent with a case definition of ARC and those reporting the name of an antihistamine drug. In order to increase the sensitivity of the system, we applied an algorithm aimed at automatically identifying jargon expressions related to medical terms. We compared weekly Twitter trends with National Allergy Bureau weekly pollen counts derived from US stations, and found a high correlation of the sum of the total pollen counts from each stations with tweets reporting ARC symptoms (Pearson’s correlation coefficient: 0.95) and with tweets reporting antihistamine drug names (Pearson’s correlation coefficient: 0.93). Longitude and latitude of the pollen stations affected the strength of the correlation. Twitter and other social networks may play a role in allergic disease surveillance and in signaling drug consumptions trends.
机译:花粉预测在世界各地都在使用,以为过敏性鼻结膜炎(ARC)患者提供治疗决策依据。我们利用了来自Twitter的数据,以便识别报告了与ARC病例定义相一致的症状组合的推文以及报告了抗组胺药名称的推文。为了提高系统的灵敏度,我们应用了一种旨在自动识别与医学术语相关的术语的算法。我们将每周的Twitter趋势与美国国家过敏局的每周花粉计数进行了比较,发现每个站点的总花粉计数总和与报告ARC症状的推文(Pearson相关系数:0.95)和与报告抗组胺药的推文高度相关。药品名称(Pearson相关系数:0.93)。花粉站的经度和纬度影响了相关强度。 Twitter和其他社交网络可能在变应性疾病监测和指示毒品消费趋势中发挥作用。

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