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 social media
platforms, as the type of users and the information offered by these platforms
can show different CES attributes. The ease of application and 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.Comment: 23 pages, 5 figures, 2 appendice
