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“有人知道这是什么物种吗?”——作为胚胎期公民科学社区的推特对话

"Anyone Know What Species This Is?" - Twitter Conversations as Embryonic Citizen Science Communities.

作者信息

Daume Stefan, Galaz Victor

机构信息

Faculty of Forest Sciences and Forest Ecology, Georg-August-University Göttingen, Büsgenweg 5, 37077 Göttingen, Germany.

Stockholm Resilience Centre, Stockholm University, SE-10691 Stockholm, Sweden.

出版信息

PLoS One. 2016 Mar 11;11(3):e0151387. doi: 10.1371/journal.pone.0151387. eCollection 2016.

Abstract

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.

摘要

诸如博客、微博或社交网络等社交媒体正越来越多地被用于调查和预测各种趋势,这些趋势不仅包括社会和自然现象,还包括环境信息。在此,我们认为通过推特发布的机会性生物多样性观测数据是此类数据挖掘中一个有前景且至今尚未被探索的例子。正如我们所阐述的,它可以为传统生态监测项目提供实时信息,包括那些通过公民科学活动获取的数据。利用为生态监测中社交媒体数据的一般评估而收集的推特数据,我们调查了一个样本,即我们所指的带有物种鉴定请求的生物多样性观测数据(N = 191)。这些数据包括作为微博服务推特上的消息发布的图片。正如我们所展示的,这些图片经常引发对话,从而导致对这些观测数据进行分类鉴定。所有分析的推文都带有物种鉴定请求,其中64%的推文得到了回复,86%的回复至少包含一个建议的鉴定结果,其中76%被评估为正确。所有发布的观测数据都包含或链接到图片,样本中81%的图片整体质量被归类为令人满意或更好,并且在71%的鉴定结果中实现了物种水平的分类鉴定。我们认为,原始消息作者和对话参与者可以被视为隐性或雏形的公民科学社区,它们作为生态监测中的机会性数据源以及公民科学项目的潜在积极贡献者,都能提供有价值的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0436/4788454/c1c83ef69375/pone.0151387.g001.jpg

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