DOI: 10.5061/dryad.cjsxksn3h
title: Data from: Understanding sentiment of national park visitors from social media data

description: National parks are key for conserving biodiversity and supporting people´s
 well-being. However, anthropogenic pressures challenge the existence of
 national parks and their conservation effectiveness. Therefore, it is
 crucial to assess how people perceive national parks in order to enhance
 socio-political support for conservation. User-generated data shared by
 visitors on social media provide opportunities to understand how people
 perceive (e.g. preferences, feelings, opinions) national parks during
 nature-based recreational experiences. In this study, we applied methods
 from automated natural language processing to assess visitors’ sentiment
 when describing experiences in Instagram posts geolocated inside four
 national parks in South Africa. We found that visitors’ sentiment was
 positive, and mostly included emotions such as joy, anticipation, trust
 and surprise, with only a small occurrence of posts with negative
 feelings. Appreciation of nature, in association with a diverse set of
 other aspects, such as activities, geographical features and tourist
 attractions, was used to describe experiences related to nature,
 wilderness, traveling, holidays and adventures. The type of nature-based
 experience described by visitors was park specific, revealing different
 profiles of parks providing wildlife or scenery experiences. Findings
 support and highlight the societal role of national parks in providing
 visitors with opportunities to develop positive connections with nature.
 Social media data may be used to understand visitors’ perceptions, and how
 the image of national parks is constructed by users in the virtual social
 environment. This may help inform management for promoting a high quality
 tourism experience, as well as conservation marketing aimed at fostering
 socio-political support for national parks and their long-term
 conservation effectiveness.
description: <strong>Data collection</strong>
 The dataset contains 33,213 Instagram posts obtained through the
 Application Programming Interface (API). Data collection was carried out
 1 week/month between June 2013 and February 2016, for posts which were
 geolocated within the bords of four National Parks in South Africa,
 namely Addo Elephant (AENP), Garden Route (GRNP), Kruger (KNP) and Table
 Mountain (TMNP) National Parks. Only publicly available posts were
 accessed and users were de-identified. The dataset contains only posts
 which were in English language.  
 <strong>Data processing</strong>
 Posts have been de-identified in order to protect users´privacy.
 For each post, text content was converted in number of
 words/hashtags. Normalized frequecies of single words/hashtags used across
 all posts per park is provided. Text content of each posts
 was assigned a sentiment values, a sentiment polarity and emotion values
 by using NRC Word-Emotion Lexicon (Mohammad & Turney 2013,
 Crowdsourcing a Word-Emotion Association Lexicon. <i>Computational
 Intelligence</i>, 23, 236–465). Please refer to the manuscript for
 further details on the methods used for classification.
  
description: The dataset is in .xlsx format and contains three
 sheets: 1- A description of the variables in the other
 sheets.  2- Social media posts and classification of
 sentiment values, polarity and emotion values  
 3- Normalized frequecies of single words/hashtags used across all
 posts per park.