“Anyone Know What Species This Is?” – Twitter Conversations as Embryonic Citizen Science Communities

Social media like blogs, micro-blogs or social networks are increasingly being investigated and employed to detect and predict trends for not only social and physical phenomena, but also to capture environmental information. Here we argue that opportunistic biodiversity observations published through Twitter represent one promising and until now unexplored example of such data mining. As we elaborate, it can contribute to real-time information to traditional ecological monitoring programmes including those sourced via citizen science activities. Using Twitter data collected for a generic assessment of social media data in ecological monitoring we investigated a sample of what we denote biodiversity observations with species determination requests (N = 191). These entail images posted as messages on the micro-blog service Twitter. As we show, these frequently trigger conversations leading to taxonomic determinations of those observations. All analysed Tweets were posted with species determination requests, which generated replies for 64% of Tweets, 86% of those contained at least one suggested determination, of which 76% were assessed as correct. All posted observations included or linked to images with the overall image quality categorised as satisfactory or better for 81% of the sample and leading to taxonomic determinations at the species level in 71% of provided determinations. We claim that the original message authors and conversation participants can be viewed as implicit or embryonic citizen science communities which have to offer valuable contributions both as an opportunistic data source in ecological monitoring as well as potential active contributors to citizen science programmes.

诸如博客、微博客及社交网络等社交媒体，正日益被研究与应用于检测、预测社会与自然现象的趋势，同时亦可用于获取环境信息。本文认为，通过Twitter发布的偶发性生物多样性观测记录，便是此类数据挖掘中一项极具前景且迄今尚未被充分探索的案例。如后文所述，该类数据可为传统生态监测项目（包括源自公民科学（citizen science）活动的项目）提供实时信息支持。本研究依托为生态监测中社交媒体数据通用评估所采集的Twitter数据集，对我们标记为“带物种鉴定请求的生物多样性观测记录”的样本（N = 191）展开了分析。此类样本均为发布于微博客平台Twitter的图文推文。如研究结果所示，此类推文往往会引发讨论，进而实现对观测对象的分类学鉴定。本研究分析的所有推文均附带物种鉴定请求，其中64%的推文获得了回复；在获得回复的推文中，86%至少包含1条鉴定建议，而这些建议中有76%被判定为正确。所有发布的观测记录均包含或关联图片，其中81%的样本的整体图像质量被评定为合格及以上；在给出的分类学鉴定结果中，71%可鉴定至物种水平。本文认为，推文原作者与讨论参与者可被视为隐性或萌芽状态的公民科学社群，其既可为生态监测提供偶发性数据源，也有望成为公民科学项目的积极参与者，贡献宝贵价值。