Abstract
The use of social media (SM) data has emerged as a promising tool for the assessment of cultural ecosystem services (CES). Most studies have focused on the use of single SM platforms and on the analysis of photo content to assess the demand for CES. Here, we introduce a novel methodology for the assessment of CES using SM data through the application of graph theory network analyses (GTNA) on hashtags associated to SM posts and compare it to photo content analysis. We applied the proposed methodology on two SM platforms, Instagram and Twitter, on three worldwide known case study areas, namely Great Barrier Reef, Galapagos Islands and Easter Island. Our results indicate that the analysis of hashtags through graph theory offers similar capabilities to photo content analysis in the assessment of CES provision and the identification of CES providers. More importantly, GTNA provides greater capabilities at identifying relational values and eudaimonic aspects associated to nature, elusive aspects for photo content analysis. In addition, GTNA contributes to the reduction of the interpreter’s bias associated to photo content analyses, since GTNA is based on the tags provided by the users themselves. The study also highlights the importance of considering data from different SM platforms, as the type of users and the information offered by these platforms can show different CES attributes. The ease of application and relative short computing processing times involved in the application of GTNA makes it a cost-effective method with the potential of being applied to large geographical scales.
Highlights
Humans are deeply connected to the oceans, the largest biome of the planet
To advance in the assessment of cultural ecosystem services (CES) provided by nature through social media (SM) data, we present a novel methodology based on the analysis of text information associated to SM posts through the application of graph theory network analysis (GTNA) techniques
The most widely used method is based on the analysis of photo content, which offers a partial vision of the range of CES offered by nature
Summary
Humans are deeply connected to the oceans, the largest biome of the planet. For centuries, humans have lived in coastal communities where people fished, gleaned and hunted for food to support their livelihoods (Erlandson and Rick, 2010). Despite differences in data content and user types, SM data mining and analysis has proven very valuable as it can provide information on how people interact with their environment, including interactions with nature (Di Minin et al, 2015; Mancini et al, 2018) people’s preferences for nature-based experiences (Hausmann et al, 2017; Oteros-Rozas et al, 2018), visitation patterns in conservation areas (Tenkanen et al, 2017; Wood et al, 2013) or on mapping CES (Clemente et al, 2019; Richards and Friess, 2015). While the number of studies focusing on the terrestrial environment is increasing, few had marine and coastal areas within their scope (Ghermandi and Sinclair, 2019; Toivonen et al, 2019)
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