Tourists' perceptions of nature and its non-material contributions to people at Mount Kilimanjaro, Tanzania using Twitter posts

This dataset was collected as part of the Kili-SES research unit (kili-ses.senckenberg.de ), Subproject 2, Work Package 2, which focuses on understanding the elements of nature that support non-material contributions, such as aesthetic enjoyment, recreation, and spirituality. Using the NCP paradigm, non-material contributions of nature to people (NCP) were identified through an inductive approach, together with the entities of nature (EN) mentioned in Twitter posts.This dataset was collected in October 2021 using the R package academictwitteR with Twitter’s official Application Programming Interface keys (API; developer.twitter.com). These are publicly available Tweets targeting Mount Kilimanjaro National Park (Tanzania) and its surroundings from 10 years (April 2011 to June 2021). Data were manually filtered and cleaned to preserve tourists' Tweets of their nature experiences at Mount Kilimanjaro, Tanzania. We employed an inductive coding approach to prevent an a priori categorization of tourists' perceived non-material NCP, resulting in a total of 15 non-material NCP context-specific sub-categories which can be linked back to the generalizing categories of the IPBES framework (2019). We classified the terms that tourists used to refer to nature into different broader (e.g., biotic, abiotic) and more specific sub-categories (e.g., mammal, plant, insect, reptiles, geological, hydrological) resulting in 15 sub-categories for entities of nature, and two human-made features (e.g., infrastructure and cultural). The final dataset contains 1255 entries, and each observation represents a Tweet that contains at least one non-material nature's contributions to people (non-material NCP) and one entity of nature perceived by an individual. For more details please refer to the Metadata.htm document. To understand the dataset of 62 columns and 1255 observations (kilimanjaro_perception_NCPEN_dataset.csv), please refer to the README.txtIn this repository you will also find an R script (kili_perception_code.R). We recommend opening the scripts in Rstudio as this will allow to automatically install the packages used. Install suggested packages, and run the script. This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), Research Unit 5064: “The role of nature for human well-being in the Kilimanjaro Social-Ecological System (Kili-SES)”. Project Number 428658210