Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Using social media to quantify nature-based tourism and recreation.

ABSTRACT: Scientists have traditionally studied recreation in nature by conducting surveys at entrances to major attractions such as national parks. This method is expensive and provides limited spatial and temporal coverage. A new source of information is available from online social media websites such as flickr. Here, we test whether this source of "big data" can be used to approximate visitation rates. We use the locations of photographs in flickr to estimate visitation rates at 836 recreational sites around the world, and use information from the profiles of the photographers to derive travelers' origins. We compare these estimates to empirical data at each site and conclude that the crowd-sourced information can indeed serve as a reliable proxy for empirical visitation rates. This new approach offers opportunities to understand which elements of nature attract people to locations around the globe, and whether changes in ecosystems will alter visitation rates.

SUBMITTER: Wood SA

PROVIDER: S-EPMC3797992 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Using social media to quantify nature-based tourism and recreation.

Wood Spencer A SA Guerry Anne D AD Silver Jessica M JM Lacayo Martin M

Scientific reports 20131017

Scientists have traditionally studied recreation in nature by conducting surveys at entrances to major attractions such as national parks. This method is expensive and provides limited spatial and temporal coverage. A new source of information is available from online social media websites such as flickr. Here, we test whether this source of "big data" can be used to approximate visitation rates. We use the locations of photographs in flickr to estimate visitation rates at 836 recreational sites ...[more]

PMID: 24131963

Similar Datasets

Using social media to quantify spatial and temporal dynamics of nature-based recreational activities.

Project description:Big data offer a great opportunity for nature-based recreation (NbR) mapping and evaluation. However, it is important to determine when and how it is appropriate to use this resource. We used Scotland as a case study to validate the use of data from Flickr as an indicator of NbR on a national scale and at several regional spatial and temporal resolutions. We compared Flickr photographs to visitor statistics in the Cairngorms National Park (CNP) and determined whether temporal variability in photo counts could be explained by known annual estimates of CNP visitor numbers. We then used a unique recent national survey of nature recreation in Scotland to determine whether the spatial distribution of Flickr photos could be explained by known spatial variability in nature use. Following this validation work, we used Flickr data to identify hotspots of wildlife watching in Scotland and investigated how they changed between 2005 and 2015. We found that spatial and temporal patterns in Flickr count are explained by measures of visitation obtained through surveys and that this relationship is reliable down to a 10 Km scale resolution. Our findings have implications for planning and management of NbR as they suggest that photographs uploaded on Flickr reflect patterns of NbR at spatial and temporal scales that are relevant for ecosystem management.

| S-EPMC6047793 | biostudies-literature

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

Project description:Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

| S-EPMC5017630 | biostudies-literature

Social Dilemmas in Nature-Based Tourism Depend on Social Value Orientations.

Project description:Nature-based tourism (NBT) is vulnerable to a rapid increase in visitors because natural resources are often open access. Market failure caused by over-exploitation of natural resources is an example of social dilemmas in common-pool resource systems. Game theory, which describes people's decision making under conflicts, has been applied to the analysis of social dilemmas in NBT. However, previous studies use non-cooperative games assuming individualistic players and discuss the emergence of social dilemmas only in a limited situation. Here, we demonstrate, by developing a two-player non-cooperative game of wildlife viewing, that the traditional game-theoretic approach fails to find social dilemmas. By analysing the competition between tour operators (players) with different social value orientations (SVOs), we found that concentration of tours becomes a Pareto-inefficient Nash equilibrium (PINE) when both players are competitive. Whether the wildlife-viewing market is a Prisoner's dilemma depends on players' SVOs. Furthermore, we found that fair punishment on competitive players promotes rather than suppresses the emergence of PINE. Our results suggest that the diversity of SVOs is an essential factor in understanding social dilemmas in NBT.

| S-EPMC7048808 | biostudies-literature

Next-generation visitation models using social media to estimate recreation on public lands.

Project description:Outdoor and nature-based recreation provides countless social benefits, yet public land managers often lack information on the spatial and temporal extent of recreation activities. Social media is a promising source of data to fill information gaps because the amount of recreational use is positively correlated with social media activity. However, despite the implication that these correlations could be employed to accurately estimate visitation, there are no known transferable models parameterized for use with multiple social media data sources. This study tackles these issues by examining the relative value of multiple sources of social media in models that estimate visitation at unmonitored sites and times across multiple destinations. Using a novel dataset of over 30,000 social media posts and 286,000 observed visits from two regions in the United States, we compare multiple competing statistical models for estimating visitation. We find social media data substantially improve visitor estimates at unmonitored sites, even when a model is parameterized with data from another region. Visitation estimates are further improved when models are parameterized with on-site counts. These findings indicate that while social media do not fully substitute for on-site data, they are a powerful component of recreation research and visitor management.

| S-EPMC7508982 | biostudies-literature

Using social media to estimate Zika's impact on tourism: #babymoon, 2014-2017.

Project description:Zika virus infection during pregnancy can cause microcephaly and other birth defects. We hypothesized that the Latin America Zika epidemic resulted in pregnant women and their partners adopting behavioral changes to limit risk, leading them to forego travel to Zika-affected locations. We evaluated this hypothesis by studying travelers' intent and behavior through Twitter data related to babymoon: a holiday taken by parents-to-be before their baby is born. We found the odds of mentioning representative Zika-affected locations in #babymoon tweets dropped significantly (Odds ratio: 0.29, 95% CI: 0.20-0.40) after the Zika-microcephaly association became well-known. This result was further corroborated through a content analysis of #babymoon tweets mentioning Zika-affected locations, which identified if the Twitter user was physically present in the Zika-affected locations. Conversely, we found a small but statistically insignificant increase in the odds of mentioning Zika-free locations from #babymoon tweets (Odds Ratio: 1.11, 95% CI: 0.97-1.27) after the Zika-microcephaly association became well-known.

| S-EPMC6383918 | biostudies-literature

Economic impact of nature-based tourism

Project description:Protected areas (PAs) can help address biodiversity loss by promoting conservation while fostering economic development through sustainable tourism. Nature-based tourism can generate economic benefits for communities in and around PAs; however, its impacts do not lend themselves to conventional impact evaluation tools. We utilize a Monte Carlo simulation approach with econometric estimations using microdata to estimate the full economic impact of nature-based tourism on the economies surrounding three terrestrial and two marine PAs. Simulations suggest that nature-based tourism creates significant economic benefits for communities around PAs, including the poorest households, and many of these benefits are indirect, via income and production spillovers. An additional tourist increases annual real income in communities near the PAs by US$169—$2,400, significantly more than the average tourist’s expenditure. Conversely, lost tourism due to the COVID-19 pandemic and economic costs of human-wildlife conflict have disproportionately large negative impacts on local incomes.

| S-EPMC10096494 | biostudies-literature

Space tourism flow generated from social media data.

Project description:The data is for empirical studies derived from a related research article about space tourism [1], which is a conceptual article with a different aim of economic measurement scale. Most space tourism research is conceptual because data from the nascent industry is limited [2]. Thus this data is constrictive for conducting empirical studies to contribute to quantitative analysis in space tourism [3]. Data from this study were collected by recruiting 361 respondents through snowball and convenient sampling targeted to samples interested in space tourism; 339 responses were adopted after the valid screening of missing data or data bias [4]. Targeted groups of potential space tourism customers were investigated to collect data through a designed questionnaire on the platform, Wenjuanxing, with a majority population database providing functions equivalent to Amazon Mechanical Turk [2]. The reliability and validity of all constructs showed that the questionnaire was proper for measurement [3]. Data analysis applied the structural equation model with Mplus to examine the CFA model and research hypothesis. Structural equation modeling was used to conduct the hypotheses test and model fitness through the statistical tool Mplus. Results imply that the data is suitable for conducting replication studies. To enlighten space tourism emergence studies, this data shows its importance for further research models [5].

| S-EPMC10051023 | biostudies-literature

BERT-based tourism named entity recognition: making use of social media for travel recommendations.

Project description:BackgroundSocial media has become a massive encyclopedia of almost anything due to its content richness. People tell stories, write comments and feedback, and share knowledge through social media. The information available on social media enables 'clueless' travelers to get quick travel recommendations in the tourism sector. Through a simple query, such as typing 'places to visit in Bali', travelers can get many blog articles to help them decide which places of interest to visit. However, doing this reading task without a helper can be overwhelming.MethodsTo overcome this problem, we developed Bidirectional Encoder Representations from Transformers (BERT)-based tourism named entity recognition system, which is used to highlight tourist destination places in the query result. BERT is a state-of-the-art machine learning framework for natural language processing that can give a decent performance in various settings and cases. Our developed tourism named entity recognition (NER) model specifies three different tourist destinations: heritage, natural, and purposefully built (man-made or artificial). The dataset is taken from various tourism-related community articles and posts.ResultsThe model achieved an average F1-score of 0.80 and has been implemented into a traveling destination recommendation system. By using this system, travelers can get quick recommendations based on the popularity of places visited in the query frame.DiscussionBased on the survey that we conducted to target respondents who have never visited and have no or limited knowledge about tourist attractions in some example cities, their average interest level from the recommendation results is higher than four on a scale of 1 to 5. Thus, it can be considered a good recommendation. Furthermore, the NER model performance is comparable to another related research.

| S-EPMC10773720 | biostudies-literature

A global perspective on trends in nature-based tourism.

Project description:Reports of rapid growth in nature-based tourism and recreation add significant weight to the economic case for biodiversity conservation but seem to contradict widely voiced concerns that people are becoming increasingly isolated from nature. This apparent paradox has been highlighted by a recent study showing that on a per capita basis, visits to natural areas in the United States and Japan have declined over the last two decades. These results have been cited as evidence of "a fundamental and pervasive shift away from nature-based recreation"-but how widespread is this phenomenon? We address this question by looking at temporal trends in visitor numbers at 280 protected areas (PAs) from 20 countries. This more geographically representative dataset shows that while PA visitation (whether measured as total or per capita visit numbers) is indeed declining in the United States and Japan, it is generally increasing elsewhere. Total visit numbers are growing in 15 of the 20 countries for which we could get data, with the median national rate of change unrelated to the national rate of population growth but negatively associated with wealth. Reasons for this reversal of growth in the richest countries are difficult to pin down with existing data, but the pattern is mirrored by trends in international tourist arrivals as a whole and so may not necessarily be caused by disaffection with nature. Irrespective of the explanation, it is clear that despite important downturns in some countries, nature-related tourism is far from declining everywhere, and may still have considerable potential both to generate funds for conservation and to shape people's attitudes to the environment.

| S-EPMC2694281 | biostudies-literature

Evidence for a fundamental and pervasive shift away from nature-based recreation.

Project description:After 50 years of steady increase, per capita visits to U.S. National Parks have declined since 1987. To evaluate whether we are seeing a fundamental shift away from people's interest in nature, we tested for similar longitudinal declines in 16 time series representing four classes of nature participation variables: (i) visitation to various types of public lands in the U.S. and National Parks in Japan and Spain, (ii) number of various types of U.S. game licenses issued, (iii) indicators of time spent camping, and (iv) indicators of time spent backpacking or hiking. The four variables with the greatest per capita participation were visits to Japanese National Parks, U.S. State Parks, U.S. National Parks, and U.S. National Forests, with an average individual participating 0.74-2.75 times per year. All four time series are in downtrends, with linear regressions showing ongoing losses of -1.0% to -3.1% per year. The longest and most complete time series tested suggest that typical declines in per capita nature recreation began between 1981 and 1991, are proceeding at rates of -1.0% to -1.3% per year, and total to date -18% to -25%. Spearman correlation analyses were performed on untransformed time series and on transformed percentage year-to-year changes. Results showed very highly significant correlations between many of the highest per capita participation variables in both untransformed and in difference models, further corroborating the general downtrend in nature recreation. In conclusion, all major lines of evidence point to an ongoing and fundamental shift away from nature-based recreation.

| S-EPMC2268130 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data