Abstract

Accounting for community opinions of environmental restoration is critical both for planning and evaluating these initiatives. While considerable research assesses the value of restoration through economic metrics focusing on expenditures or preferences for ecosystem services, these metrics may not adequately account for the sociocultural services that ecosystems provide communities, such as mental and physical health or recreational opportunities. To address this challenge, we explored the use of social media data to assess online discourse communities’ opinions about ecosystem services through a case study of Twitter mentions of sites targeted for restoration through the Great Lakes Restoration Initiative (GLRI). While there is evidence of the economic and ecological benefits of GLRI, little is known about how these benefits at sites targeted for funding are perceived by the public. From April through October 2019, we collected 40,000 tweets that mentioned an Area of Concern or a Great Lakes National Park that received GLRI funding. We used a mixed-methodological approach combining tweet content and sentiment analysis to determine themes of discussion and characterize online discourse communities’ opinions around these topics. Half of all tweets were about one of three Areas of Concern, and recreation was the most discussed theme with an overall positive sentiment. A metric accounting for the number of tweets and the sentiment of tweets was derived to understand community opinions of restoration at these areas. Our findings demonstrate the potential of social media data mining as a tool for examining online conversations about and engagement with the Great Lakes.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.