NDLI: Using social media for collaborative species identification and occurrence: issues, methods, and tools

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Using social media for collaborative species identification and occurrence: issues, methods, and tools

Content Provider	ACM Digital Library
Author	Chuang, Tyng-Ruey Lemmens, Rob Mai, Guan-Shuo Shao, Kwang-Tsao Lin, Te-En Kraak, Menno-Jan Hsu, Cheng-Hsin Deng, Dong-Po Lin, Hsu-Hong
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.
Starting Page	22
Ending Page	29
Page Count	8
File Format	PDF
ISBN	9781450316941
DOI	10.1145/2442952.2442957
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-11-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Volunteered geographic information Citizen science Linking open data Social media Facebook
Content Type	Text
Resource Type	Article

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