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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46043

Title: Using Social Media for Collaborative Species identification and Occurrence: Issues, Methods, and Tools
Authors: Dong-Po Deng
Tyng-Ruey Chuang
Kwang-Tsao Shao
Guan-Shuo Mai
Te-En Lin
Rob Lemmens
Cheng-Hsin Hsu
Hsu-Hong Lin
Menno-Jan Kraak
Contributors: 國立臺灣海洋大學:海洋生物研究所
Keywords: Structured programming
Citizen science
Social media
Information extraction
Data structure
Date: 2012
Issue Date: 2018-04-23T06:27:58Z
Abstract: Abstract: The emergence of social media enables people to interact with others on the web in ways that are media-rich ("updates" or "posts" can be text, photo, audio, video, etc), time-shifted (correspondence need not happen at once or within a pre-defined time frame), and social in nature. By utilizing social media, citizen science projects can potentially engage many participants to contribute their observations covering a large geographic region and over a long time period. This is an improvement, for example, over traditional biodiversity surveys which typically involve relatively few people in confined regions and periods.
As social media is not designed for scientific data collection and analysis, there is a problem in transferring unstructured information items (e.g. free-form text, unidentified images, etc.) often found in social media to structured data records for scientific tasks. To help bridge this gap, we propose an approach comprised of three steps: (1) Information Extraction, (2) Information Formalization, and (3) Information Reuse. We apply this approach to processing posts and comments from two Facebook interest groups on species observations. Our study demonstrates that with principled methods and proper tools, crowdsourced social media contents such as those from Facebook interest groups can be used for collaborative species identification and occurrence.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46043
Appears in Collections:[海洋生物研究所] 期刊論文

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