Limits of use of social media for monitoring biosecurity events

Compared to applications that trigger massive information streams, like earthquakes and human disease epidemics, the data input for agricultural and environmental biosecurity events (ie. the introduction of unwanted exotic pests and pathogens), is expected to be sparse and less frequent. To investigate if Twitter data can be useful for the detection and monitoring of biosecurity events, we adopted a three-step process. First, we confirmed that sightings of two migratory species, the Bogong moth (Agrotis infusa) and the Common Koel (Eudynamys scolopaceus) are reported on Twitter. Second, we developed search queries to extract the relevant tweets for these species. The queries were based on either the taxonomic name, common name or keywords that are frequently used to describe the species (symptomatic or syndromic). Third, we validated the results using ground truth data. Our results indicate that the common name queries provided a reasonable number of tweets that were related to the grou...相较于地震、人类疾病疫情等可催生海量信息流的应用场景，农业与环境生物安全（biosecurity）事件（即外来有害生物与病原体的入侵）的数据输入通常较为稀疏且发生频率较低。为探究推特（Twitter）数据能否用于生物安全事件的检测与监测，本研究采用了三步研究流程：其一，证实推特平台上存在两种迁徙物种——博贡蛾（Agrotis infusa）与普通噪鹃（Eudynamys scolopaceus）的目击记录；其二，针对这两个物种构建了相关推文提取搜索词，搜索词的构建依据涵盖物种的学名（taxonomic name）、常用名（common name），以及用于描述该物种的高频表征性或综合征性关键词；其三，采用基准真值数据（ground truth data）对研究结果进行验证。本研究结果显示，基于常用名构建的搜索词可获取到数量合理的与该类群相关的推文（原文内容截断）