Scientific papers dedicated to conservation culturomics

The presented list does not represent an endorsement of the papers or their content

2022

• Alieva, D., Holgado, D., de Juan, S., Ruiz-Frau, A., Villasante, S., Maya-Jariego, I., 2022. Assessing landscape features and ecosystem services of marine protected areas through photographs on social media: comparison of two archipelagos in Spain. Environment, Development and Sustainability 24, 9623-9641.
• Akasaka, M., Kubo, T., Soga, M., 2022. How well does online information-seeking behavior indicate public conservation orientation? Taxonomy and personal characteristics matter. Journal for Nature Conservation, 126123.
• Azevedo, A.K., Vieira, F.A., Guedes-Santos, J., Gaia, J.A., Pinheiro, B.R., Bragagnolo, C., Correia, R.A., Ladle, R.J., Malhado, A., 2022. A big data approach to identify the loss of coastal cultural ecosystem services caused by the 2019 Brazilian oil spill disaster. Anais da Academia Brasileira de Ciências 94.
• Barros, C., Gutiérrez, J., García-Palomares, J., 2022. Geotagged data from social media in visitor monitoring of protected areas; a scoping review. Current Issues in Tourism 25, 1399-1415.
• Bayón, Á., Godoy, O., Vilà, M., 2022. Invasion risks and social interest of non-native woody plants in urban parks of mainland Spain. Anales del Jardín Botánico de Madrid 79, e121.
• Bergman, J.N., Buxton, R.T., Lin, H.-Y., Lenda, M., Attinello, K., Hajdasz, A.C., Rivest, S.A., Nguyen, T.T., Cooke, S.J., Bennett, J.R., Clements, J.C., 2022. Evaluating the benefits and risks of social media for wildlife conservation. FACETS 7, 360-397.
• Bhatt, P., Pickering, C.M., 2022. Destination image of Chitwan National Park, Nepal: Insights from a content analysis of online photographs. Journal of Outdoor Recreation and Tourism 37, 100488.
• Borowiec, M.L., Dikow, R.B., Frandsen, P.B., McKeeken, A., Valentini, G., White, A.E., 2022. Deep learning as a tool for ecology and evolution. Methods in Ecology and Evolution 13, 1640-1660.
• Burke, R., Sherwood, O.L., Clune, S., Carroll, R., McCabe, P.F., Kane, A., Kacprzyk, J., 2022. Botanical boom: A new opportunity to promote the public appreciation of botany. Plants, People, Planet.
• Cao, H., Wang, M., Su, S., Kang, M., 2022. Explicit quantification of coastal cultural ecosystem services: A novel approach based on the content and sentimental analysis of social media. Ecological Indicators 137, 108756.
• Cardoso, A.S., Renna, F., Moreno-Llorca, R., Alcaraz-Segura, D., Tabik, S., Ladle, R.J., Vaz, A.S., 2022. Classifying the content of social media images to support cultural ecosystem service assessments using deep learning models. Ecosystem Services 54, 101410.
• Cerri, J., Carnevali, L., Monaco, A., Genovesi, P., Bertolino, S., 2022. Blacklists do not necessarily make people curious about invasive alien species. A case study with Bayesian structural time series and Wikipedia searches about invasive mammals in Italy. NeoBiota 71.
• Chang, C.H., Armsworth, P.R., Masuda, Y.J., 2022. Environmental Discourse Exhibits Consistency and Variation across Spatial Scales on Twitter. Bioscience.
• Chang, C.H., Armsworth, P.R., Masuda, Y.J., 2022. Twitter data reveal six distinct environmental personas. Frontiers in Ecology and the Environment.
• Chang, P., Olafsson, A.S., 2022. The scale effects of landscape variables on landscape experiences: a multi-scale spatial analysis of social media data in an urban nature park context. Landscape Ecology 37, 1271-1291.
• Child, K.R., Darimont, C.T., 2015. Hunting for Trophies: Online Hunting Photographs Reveal Achievement Satisfaction with Large and Dangerous Prey. Human Dimensions of Wildlife 20, 531-541.
• Farrell, M.J., Brierley, L., Willoughby, A., Yates, A., Mideo, N., 2022. Past and future uses of text mining in ecology and evolution. Proceedings of the Royal Society B: Biological Sciences 289, 20212721.
• Fox, N., Graham, L.J., Eigenbrod, F., Bullock, J.M., Parks, K.E., 2022. Geodiversity Supports Cultural Ecosystem Services: an Assessment Using Social Media. Geoheritage 14, 27.
• Ghermandi, A., 2022. Geolocated social media data counts as a proxy for recreational visits in natural areas: A meta-analysis. Journal of Environmental Management 317, 115325.
• Ghermandi, A., Depietri, Y., Sinclair, M., 2022. In the AI of the beholder: A comparative analysis of computer vision-assisted characterizations of human-nature interactions in urban green spaces. Landscape and Urban Planning 217, 104261.
  
• Grant, M.I., Bicknell, A.W.J., Htut, T., Maung, A., Maung, T., Myo Myo, K., Rein, T., San, M.K., White, W.T., Ya, K.Z., Mizrahi, M., 2022. Market surveys and social media provide confirmation of the endangered giant freshwater whipray Urogymnus polylepis in Myanmar. Journal of Fish Biology 101, 302-307.
  
• Hartmann, M.C., Koblet, O., Baer, M.F., Purves, R.S., 2022. Automated motif identification: Analysing Flickr images to identify popular viewpoints in Europe’s protected areas. Journal of Outdoor Recreation and Tourism 37, 100479.
• Hartmann, M.C., Schott, M., Dsouza, A., Metz, Y., Volpi, M., Purves, R.S., 2022. A text and image analysis workflow using citizen science data to extract relevant social media records: Combining red kite observations from Flickr, eBird and iNaturalist. Ecological Informatics 71, 101782.
• Harywanto, G.N., Veron, J.S., Suhartono, D., 2022. A BERTweet-based design for monitoring behaviour change based on five doors theory on coral bleaching campaign. Journal of Big Data 9, 73.
• Havinga, I., Marcos, D., Bogaart, P.W., Hein, L., Tuia, D., 2021. Social media and deep learning capture the aesthetic quality of the landscape. Scientific Reports 11, 20000.
• Heikinheimo, V., Järv, O., Tenkanen, H., Hiippala, T., Toivonen, T., 2022. Detecting country of residence from social media data: a comparison of methods. International Journal of Geographical Information Science, 1-22.
• Hickman, C.R., Unger, S.D., 2022. Societal attitudes towards hellbender salamander conservation The roles of traditional and social media, In Communicating endangered species: Extinction, News and Public Policy. eds E. Freedman, S.S. Hiles, D.B. Sachsman, pp. 166-183.
• Holmes, B., Strzelecki, A., Springer, S., Zieger, M., 2022. Google Trends data reveal a sharp trend: teeth and claws attract more interest than feathers, hooves or fins. Environmental Conservation, 1-9.
• Howard, L., van Rees, C.B., Dahlquist, Z., Luikart, G., Hand, B.K., 2022. A review of invasive species reporting apps for citizen science and opportunities for innovation. NeoBiota 71.
• Huai, S., Van de Voorde, T., 2022. Which environmental features contribute to positive and negative perceptions of urban parks? A cross-cultural comparison using online reviews and Natural Language Processing methods. Landscape and Urban Planning 218, 104307.
• Jarić, I., Roll, U., Bonaiuto, M., Brook, B.W., Courchamp, F., Firth, J.A., Gaston, K.J., Heger, T., Jeschke, J.M., Ladle, R.J., Meinard, Y., Roberts, D.L., Sherren, K., Soga, M., Soriano-Redondo, A., Veríssimo, D., Correia, R.A., 2022. Societal extinction of species. Trends in Ecology & Evolution.
• Jensen, P.M., Danielsen, F., Skarphedinsson, S., 2022. Monitoring Temporal Trends in Internet Searches for "Ticks" across Europe by Google Trends: Tick-Human Interaction or General Interest? Insects 13, 176.
• Karasov, O., Heremans, S., Külvik, M., Domnich, A., Burdun, I., Kull, A., Helm, A., Uuemaa, E., 2022. Beyond land cover: How integrated remote sensing and social media data analysis facilitates assessment of cultural ecosystem services. Ecosystem Services 53, 101391.
• Kikuchi, Y., Nishimura, I., Sasaki, T., 2022. Wild birds in YouTube videos: Presence of specific species contributes to increased views. Ecological Informatics 71, 101767.
• Kong, I., Sarmiento, F.O., 2022. Utilizing a crowdsourced phrasal lexicon to identify cultural ecosystem services in El Cajas National Park, Ecuador. Ecosystem Services 56, 101441.
• Lee, H., Seo, B., Cord, A.F., Volk, M., Lautenbach, S., 2022. Using crowdsourced images to study selected cultural ecosystem services and their relationships with species richness and carbon sequestration. Ecosystem Services 54, 101411.
• Lennox, R.J., Sbragaglia, V., Vollset, K.W., Sortland, L.K., McClenachan, L., Jarić, I., Guckian, M.L., Ferter, K., Danylchuk, A.J., Cooke, S.J., Arlinghaus, R., Twardek, W.M., 2022. Digital fisheries data in the Internet age: Emerging tools for research and monitoring using online data in recreational fisheries. Fish and Fisheries.
• Li, Y., Xie, L., Zhang, L., Huang, L., Lin, Y., Su, Y., AmirReza, S., He, S., Zhu, C., Li, S., Gan, M., Huang, L., Wang, K., Zhang, J., Chen, X., 2022. Understanding different cultural ecosystem services: An exploration of rural landscape preferences based on geographic and social media data. Journal of Environmental Management 317, 115487.
• Liconti, A., Pittman, S.J., Rees, S.E., Mieszkowska, N., 2022. Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis. Diversity and Distributions 28, 1430-1444.
• Llanos-Paez, O., Acuña, V., 2022. Analysis of the socio-ecological drivers of the recreational use of temporary streams and rivers. Science of the Total Environment 807, 150805.
• Mammola, S., et al. 2022. An expert-curated global database of online newspaper articles on spiders and spider bites. Scientific Data 9, 109.
• Mangachena, J.R., Chauvenet, A.L.M., Pickering, C.M., 2022. Destination Images of Africa Reflected in Social Media Photographs. Society & Natural Resources, 1-19.
• Manley, K., Egoh, B.N., 2022. Mapping and modeling the impact of climate change on recreational ecosystem services using machine learning and big data. Environmental Research Letters 17, 054025.
• Marine, N., Arnaiz-Schmitz, C., Santos-Cid, L., Schmitz, M.F., 2022. Can We Foresee Landscape Interest? Maximum Entropy Applied to Social Media Photographs: A Case Study in Madrid. Land 11, 715.
• Montenegro-Hoyos, A.C., Muñoz-Carvajal, E.A., Wallberg, B.N., Seguel, M.E., Rosales, S.A., Viña-Trillos, N.A., Torres-Avilés, D.S., Villarroel, A.E., Gaymer, C.F., Squeo, F.A., 2022. Biodiversity in Times of COVID-19 and its Relationship with the Socio-Economic and Health Context: A Look from the Digital Media. Environmental Management.
• Monteiro, L.C.N., Cabral, P., 2022. Assessing Informal Trails Impacts and Fragmentation Effects on Protected Areas using Volunteered Geographic Information, In Proceedings of the 8th International Conference on Geographical Information Systems Theory, Applications and Management. pp. 48-55. SciTePress-Science and Technology Publications.
• Muller, J.R., Selier, S.-A.J., Drouilly, M., Broadfield, J., Leighton, G.R.M., Amar, A., Naude, V.N., The hunter and the hunted: Using web-sourced imagery to monitor leopard (Panthera pardus pardus) trophy hunting. Conservation Science and Practice, e12789.
• Nanni, V., Mammola, S., Macías-Hernández, N., Castrogiovanni, A., Salgado, A.L., Lunghi, E., Ficetola, G.F., Modica, C., Alba, R., Spiriti, M.M., Holtze, S., de Mello, É.M., De Mori, B., Biasetti, P., Chamberlain, D., Manenti, R., 2022. Global response of conservationists across mass media likely constrained bat persecution due to COVID-19. Biological Conservation 272, 109591.
• Nolan, G., Kane, A., Fernández-Bellon, D., 2022. Natural history films generate more online interest in depicted species than in conservation messages. People and Nature.
• Paliska, D., Kerma, S., Drobne, S., 2022. Identifying visitor mobility patterns in Slovenia using Flickr data. Geodetski Vestnik 66, 175-188.
• Park, J.-K., Park, W.-B., Do, Y., 2022. Identifying Popular Frogs and Attractive Frog Calls from YouTube Data. Sustainability 14, 10258.
• Paudel, K., Hinsley, A., Veríssimo, D., Milner-Gulland, E., 2022. Evaluating the reliability of media reports for gathering information about illegal wildlife trade seizures. PeerJ 10, e13156.
• Phillips, B.B., Burgess, K., Willis, C., Gaston, K.J., 2022. Monitoring public engagement with nature using Google Trends. People and Nature.
• Pokharel, S.S., Sharma, N., Sukumar, R., 2022. Viewing the rare through public lenses: insights into dead calf carrying and other thanatological responses in Asian elephants using YouTube videos. Royal Society Open Science 9, 211740.
• Richards, D.R., Lavorel, S., 2022. Integrating social media data and machine learning to analyse scenarios of landscape appreciation. Ecosystem Services 55, 101422.
• Santos, T., Nogueira Mendes, R., Farías-Torbidoni, E.I., Julião, R.P., Pereira da Silva, C., 2022. Volunteered Geographical Information and Recreational Uses within Metropolitan and Rural Contexts. ISPRS International Journal of Geo-Information 11, 144.
• Sbragaglia, V., Espasandín, L., Coco, S., Felici, A., Correia, R.A., Coll, M., Arlinghaus, R., 2022. Recreational angling and spearfishing on social media: insights on harvesting patterns, social engagement and sentiments related to the distributional range shift of a marine invasive species. Reviews in Fish Biology and Fisheries.
• Schaub, S., 2022. Global relationships between time preference and environmental policy performance. Environmental Science & Policy 128, 102-109.
• Shan, S., Ju, X., Wei, Y., Wen, X., 2022. Concerned or Apathetic? Using Social Media Platform (Twitter) to Gauge the Public Awareness about Wildlife Conservation: A Case Study of the Illegal Rhino Trade. International Journal of Environmental Research and Public Health 19, 6869.
  
• Shaw, M.N., Borrie, W.T., McLeod, E.M., Miller, K.K., 2022. Wildlife Photos on Social Media: A Quantitative Content Analysis of Conservation Organisations' Instagram Images. Animals 12, 1787.
  
• Shin, N., Kotani, A., Maruya, Y., Gavrilyeva, T., 2022. Can Yandex statistics and google trends be used to detect people's interests in berries in the Russian Far East? Polar Science, 100871.
• Song, Y., Ning, H., Ye, X., Chandana, D., Wang, S., 2022. Analyze the usage of urban greenways through social media images and computer vision. Environment and Planning B: Urban Analytics and City Science 49, 1682-1696.
• Svoray, T., Dorman, M., Abu-Kaf, S., Shahar, G., Gifford, R., 2022. Nature and happiness in an individualist and a collectivist culture. Scientific Reports 12, 7701.
• Teles da Mota, V., Pickering, C., Chauvenet, A., 2022. Popularity of Australian beaches: Insights from social media images for coastal management. Ocean & Coastal Management 217, 106018.
• Troumbis, A.Y., Iosifidis, S., Kalloniatis, C., 2022. Uncovering patterns of public perceptions towards biodiversity crime using conservation culturomics. Crime, Law and Social Change.
• Urzedo, D., Westerlaken, M., Gabrys, J., 2022. Digitalizing forest landscape restoration: a social and political analysis of emerging technological practices. Environmental Politics, 1-26.
• Vins, M., Aldecoa, M., Hines, H.N., 2022. Sharing wildlife conservation through 4 billion views on YouTube. Global Ecology and Conservation 33, e01970.
• Wilkins, E.J., Van Berkel, D., Zhang, H., Dorning, M.A., Beck, S.M., Smith, J.W., 2022. Promises and pitfalls of using computer vision to make inferences about landscape preferences: Evidence from an urban-proximate park system. Landscape and Urban Planning 219, 104315.
• Winder, S.G., Lee, H., Seo, B., Lia, E.H., Wood, S.A., 2022. An open-source image classifier for characterizing recreational activities across landscapes. People and Nature.
• You, S., Zheng, Q., Chen, B., Xu, Z., Lin, Y., Gan, M., Zhu, C., Deng, J., Wang, K., 2022. Identifying the spatiotemporal dynamics of forest ecotourism values with remotely sensed images and social media data: A perspective of public preferences. Journal of Cleaner Production 341, 130715.
• Young, N., Roche, D.G., Lennox, R.J., Bennett, J.R., Cooke, S.J., 2022. Ethical ecosurveillance: Mitigating the potential impacts on humans of widespread environmental monitoring. People and Nature.
• Yu, C., Lian, T., Geng, H., Li, S., 2022. Analyzing the structure of tourism destination network based on digital footprints: taking Guilin, China as a case. Data Technologies and Applications.
• Zabelskyte, G., Kabisch, N., Stasiskiene, Z., 2022. Patterns of Urban Green Space Use Applying Social Media Data: A Systematic Literature Review. Land 11, 238.
• Zhang, J., Cheng, Y., Mao, Y., Cai, W., Zhao, B., 2022. What are the factors influencing recreational visits to national forest parks in China? Experiments using crowdsourced geospatial data. Urban Forestry & Urban Greening 72, 127570.

2021

• Amiraslani, F., Dragovich, D., 2021. Wildlife and Newspaper Reporting in Iran: A Data Analysis Approach. Animals 11, 1487.
• Arkema, K.K., Fisher, D.M., Wyatt, K., Wood, S.A., Payne, H.J., 2021. Advancing Sustainable Development and Protected Area Management with Social Media-Based Tourism Data. Sustainability 13, 2427.
• Arts, I., Fischer, A., Duckett, D., van der Wal, R., 2021. The Instagrammable outdoors – Investigating the sharing of nature experiences through visual social media. People and Nature.
• Ballejo, F., Plaza, P.I., Lambertucci, S.A., 2021. Framing of visual content shown on popular social media may affect viewers’ attitudes to threatened species. Scientific Reports 11, 13512.
• Barrios-O'Neill, D., 2021. Focus and social contagion of environmental organization advocacy on Twitter. Conservation Biology Conservation Biology 35, 307-315.
• Bhatt, P., Pickering, C.M., 2021. Public Perceptions about Nepalese National Parks: A Global Twitter Discourse Analysis. Society & Natural Resources 34, 685-702.
• Boldrocchi, G., Storai, T., 2021. Data-mining social media platforms highlights conservation action for the Mediterranean Critically Endangered blue shark Prionace glauca. Aquatic Conservation: Marine and Freshwater Ecosystems 31, 3087-3099.
• Boyer, A.-L., Vaudor, L., Le Lay, Y.-F., Marty, P., 2021. Building Consensus? The Production of a Water Conservation Discourse Through Twitter: The Water use it Wisely Campaign in Arizona. Environmental Communication 15, 285-300.
• Carpentier, N., Doudaki, V., Rozsypal Pajerová, A., 2021. Conflicting and entangled human–nature relationships: A discursive-material analysis of the documentary film Kiruna - A Brand New World. People and Nature 3, 1166-1178.
• Cerri, J., Mori, E., Ancillotto, L., Russo, D., Bertolino, S., COVID-19, media coverage of bats and related Web searches: a turning point for bat conservation? Mammal Review.
• Chen, C.-F., Shi, W., Yang, J., Fu, H.-H., 2021. Social bots’ role in climate change discussion on Twitter: Measuring standpoints, topics, and interaction strategies. Advances in Climate Change Research 12, 913-923.
• Chen, Y., Sherren, K., Smit, M., Lee, K.Y., Using social media images as data in social science research. New Media & Society 0, 14614448211038761.
• Chua, M.A.H., Tan, A., Carrasco, L.R., 2021. Species awareness days: Do people care or are we preaching to the choir? Biological Conservation 255, 109002.
• Ciesielski, M., Stereńczak, K., 2021. Using Flickr data and selected environmental characteristics to analyse the temporal and spatial distribution of activities in forest areas. Forest Policy and Economics 129, 102509.
• Correia, R.A., Ladle, R., Roll, U., 2021. Special Section: Advancing Conservation Culturomics- Introduction. Conservation Biology.
• Correia, R.A., Ladle, R., Jarić, I., Malhado, A.C.M., Mittermeier, J.C., Roll, U., Soriano-Redondo, A., Veríssimo, D., Fink, C., Hausmann, A., Guedes-Santos, J., Vardi, R., Di Minin, E., 2021. Digital data sources and methods for conservation culturomics. Conservation Biology.
• Cui, N., Malleson, N., Houlden, V., Comber, A., 2021. Using VGI and Social Media Data to Understand Urban Green Space: A Narrative Literature Review. ISPRS International Journal of Geo-Information 10, 425.
• Davies, A., Hinsley, A., Nuno, A., Martin, R.O., Identifying opportunities for expert-mediated triangulation in monitoring wildlife trade on social media. Conservation Biology.
• de Juan, S., Ospina-Álvarez, A., Villasante, S., Ruiz-Frau, A., 2021. A Graph Theory approach to assess nature’s contribution to people at a global scale. Scientific Reports 11, 9118.
• Depietri, Y., Ghermandi, A., Campisi-Pinto, S., Orenstein, D.E., 2021. Public participation GIS versus geolocated social media data to assess urban cultural ecosystem services: Instances of complementarity. Ecosystem Services 50, 101277.
• Di Minin, E., Fink, C., Hausmann, A., Kremer, J., Kulkarni, R., 2021. How to address data privacy concerns when using social media data in conservation science. Conservation Biology.
• Di Minin, E., Correia, R.A., Toivonen, T., 2021. Conservation geography. Trends in Ecology & Evolution.
• Dudzińska, M., Dawidowicz, A., 2021. Detecting the Severity of Socio-Spatial Conflicts Involving Wild Boars in the City Using Social Media Data. Sensors 21, 8215.
• Durso, A.M., et al., 2021. Citizen science and online data: Opportunities and challenges for snake ecology and action against snakebite. Toxicon: X, 100071.
• Editorial, 2021. The powers and perils of using digital data to understand human behaviour. Nature 595, 149-150.
• Edwards, T., Jones, C.B., Perkins, S.E., Corcoran, P., 2021. Passive citizen science: The role of social media in wildlife observations. PLoS ONE 16, e0255416.
• Egarter Vigl, L., Marsoner, T., Giombini, V., Pecher, C., Simion, H., Stemle, E., Tasser, E., Depellegrin, D., 2021. Harnessing artificial intelligence technology and social media data to support Cultural Ecosystem Service assessments. People and Nature 3, 673-685.
• Egorova, E., 2021. Using textual volunteered geographic information to model nature-based activities: A case study from Aotearoa New Zealand. Journal of Spatial Information Science, 25-63.
• Falk, M.T., Hagsten, E., 2021. Visitor flows to World Heritage Sites in the era of Instagram. Journal of Sustainable Tourism 29, 1547-1564.
• Fink, C., Toivonen, T., Correia, R.A., Di Minin, E., 2021. Mapping the online songbird trade in Indonesia. Applied Geography 134, 102505.
• Fisher, J.C., Yoh, N., Kubo, T., Rundle, D., 2021. Could Nintendo’s Animal Crossing be a tool for conservation messaging? People and Nature 3, 1218-1228.
• Foos, F., Kostadinov, L., Marinov, N., Schimmelfennig, F., 2021. Does Social Media Promote Civic Activism? A Field Experiment with a Civic Campaign. Political Science Research and Methods 9, 500-518.
• Fox, N., Graham, L.J., Eigenbrod, F., Bullock, J.M., Parks, K.E., 2021. Reddit: A novel data source for cultural ecosystem service studies. Ecosystem Services 50, 101331.
• Fox, N., Graham, L.J., Eigenbrod, F., Bullock, J.M., Parks, K.E., 2021. Enriching social media data allows a more robust representation of cultural ecosystem services. Ecosystem Services 50, 101328.
• Freund, C.A., Heaning, E.G., Mulrain, I.R., McCann, J.B., DiGiorgio, A.L., 2021. Building better conservation media for primates and people: A case study of orangutan rescue and rehabilitation YouTube videos. People and Nature.
• Fukano, Y., Soga, M., Fukuda, M., Takahashi, Y., Koyama, M., Arakawa, Y., Miyano, N., Akiba, Y., Horiguchi, M., 2021. Debut of an endangered bird in zoos raises public interest, awareness and conservation knowledge of the species. Animal Conservation.
• Goodbody, T.R.H., Coops, N.C., Srivastava, V., Parsons, B., Kearney, S.P., Rickbeil, G.J.M., Stenhouse, G.B., 2021. Mapping recreation and tourism use across grizzly bear recovery areas using social network data and maximum entropy modelling. Ecological Modelling 440, 109377.
• Grzyb, T., Kulczyk, S., Derek, M., Woźniak, E., 2021. Using social media to assess recreation across urban green spaces in times of abrupt change. Ecosystem Services 49, 101297.
• Guedes-Santos, J., Correia, R.A., Jepson, P., Ladle, R.J., 2021. Evaluating Public Interest in Protected Areas using Wikipedia Page Views. Journal for Nature Conservation, 126040.
• Guedes-Santos, J., Aleixo Correia, R., Mendes Malhado, A.C., Ladle, R.J., 2021. A digital approach to quantifying political vulnerability of protected areas. Environmental Science & Policy 124, 616-626.
• Hautea, S., Parks, P., Takahashi, B., Zeng, J., 2021. Showing They Care (Or Don’t): Affective Publics and Ambivalent Climate Activism on TikTok. Social Media + Society 7, 20563051211012344.
• Havinga, I., Bogaart, P.W., Hein, L., Tuia, D., 2020. Defining and spatially modelling cultural ecosystem services using crowdsourced data. Ecosystem Services 43, 101091.
• Heathcote, G., 2021. Animals of Instagram: taxonomic bias in science communication online. Jcom-Journal of Science Communication 20.
• Huertas Herrera, A., Toro Manríquez, M., Soler, R., Lorenzo, C., Lencinas, M.V., Martínez Pastur, G., 2021. Assessing Socio-ecological Systems Using Social Media Data: An Approach for Forested Landscapes in Tierra del Fuego, Argentina. Social Indicators Research 157, 817-839.
• Jarić, I., Bellard, C., Correia, R.A., Courchamp, F., Douda, K., Essl, F., Jeschke, J.M., Kalinkat, G., Kalous, L., Lennox, R.J., Novoa, A., Proulx, R., Pyšek, P., Soriano–Redondo, A., Souza, A.T., Vardi, R., Veríssimo, D., Roll, U., 2021. Invasion Culturomics and iEcology. Conservation Biology.
• Jarratt, D., 2021. An exploration of webcam-travel: Connecting to place and nature through webcams during the COVID-19 lockdown of 2020. Tourism and Hospitality Research 21, 156-168.
• Jaung, W., Carrasco, L.R., 2021. Using mobile phone data to examine weather impacts on recreational ecosystem services in an urban protected area. Scientific Reports 11, 5544.
• Johnson, T.F., Kent, H., Hill, B.M., Dunn, G., Dommett, L., Penwill, N., Francis, T., González-Suárez, M., 2021. classecol: Classifiers to understand public opinions of nature. Methods in Ecology and Evolution 12, 1329-1334.
• Kaiser, N.N., Ghermandi, A., Feld, C.K., Hershkovitz, Y., Palt, M., Stoll, S., 2021. Societal benefits of river restoration – Implications from social media analysis. Ecosystem Services 50, 101317.
• Kim, G.S., Chun, J., Kim, Y., Kim, C.-K., 2021. Coastal Tourism Spatial Planning at the Regional Unit: Identifying Coastal Tourism Hotspots Based on Social Media Data. ISPRS International Journal of Geo-Information 10, 167.
• Kim, J., Son, Y., 2021. Assessing and mapping cultural ecosystem services of an urban forest based on narratives from blog posts. Ecological Indicators 129, 107983.
• Komossa, F., Wartmann, F.M., Verburg, P.H., 2021. Expanding the toolbox: Assessing methods for local outdoor recreation planning. Landscape and Urban Planning 212, 104105.
• Kotani, A., Shin, N., Tei, S., Makarov, A., Gavrilyeva, T., 2021. Seasonality in Human Interest in Berry Plants Detection by Google Trends. Frontiers in Forests and Global Change 4.
• Kovalenko, K.E., Pelicice, F.M., Kats, L.B., Kotta, J., Thomaz, S.M., 2021. Aquatic invasive species: introduction to the Special Issue and dynamics of public interest. Hydrobiologia 848, 1939-1953.
• Kroetz, A.M., Brame, A.B., Bernanke, M., McDavitt, M.T., Wiley, T.R., 2021. Tracking public interest and perceptions about smalltooth sawfish conservation in the USA using Instagram. Aquatic Conservation: Marine and Freshwater Ecosystems.
• Kubo, T., Uryu, S., Yamano, H., Tsuge, T., Yamakita, T., Shirayama, Y., 2020. Mobile phone network data reveal nationwide economic value of coastal tourism under climate change. Tourism Management 77, 104010.
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2020

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2019

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• Becken, S., Connolly, R.M., Chen, J., Stantic, B., 2019. A hybrid is born: Integrating collective sensing, citizen science and professional monitoring of the environment. Ecological Informatics 52, 35-45.
• Bernetti, I., Chirici, G., Sacchelli, S., 2019. Big data and evaluation of cultural ecosystem services: an analysis based on geotagged photographs from social media in Tuscan forest (Italy). iForest - Biogeosciences and Forestry 12, 98-105.
• Bubalo, M., van Zanten, B.T., Verburg, P.H., 2019. Crowdsourcing geo-information on landscape perceptions and preferences: A review. Landscape and Urban Planning 184, 101-111.
• Calcagni, F., Amorim Maia, A.T., Connolly, J.J.T., Langemeyer, J., 2019. Digital co-construction of relational values: understanding the role of social media for sustainability. Sustainability science 14, 1309-1321.
• Chen, Y., Parkins, J.R., Sherren, K., 2019. Leveraging Social Media to Understand Younger People’s Perceptions and Use of Hydroelectric Energy Landscapes. Society & Natural Resources 32, 1114-1122.
• Clark, M., Wilkins, E.J., Dagan, D.T., Powell, R., Sharp, R.L., Hillis, V., 2019. Bringing forecasting into the future: Using Google to predict visitation in U.S. national parks. Journal of Environmental Management 243, 88-94.
• Cooper, M. W., E. Di Minin, A. Hausmann, S. Qin, A. J. Schwartz, and R. A. Correia. 2019. Developing a global indicator for Aichi Target 1 by merging online data sources to measure biodiversity awareness and engagement. Biological Conservation 230:29-36.
• Correia RA, Di Minin E, Jarić I, Jepson P, Ladle R, Mittermeier J, Roll U, Soriano-Redondo A, Veríssimo D. 2019. Inferring public interest from search engine data requires caution. Frontiers in Ecology and the Environment 17:254-255.
• De Frenne P, Van Langenhove L, Van Driessche A, Bertrand C, Verheyen K, Vangansbeke P. 2018. Using archived television video footage to quantify phenology responses to climate change. Methods in Ecology and Evolution 9:1874-1882.
• Do, Y. 2019. Valuating aesthetic benefits of cultural ecosystem services using conservation culturomics. Ecosystem Services 36:100894.
• Do, Y., Kim, J.B., Shim, J., Kim, C.-J., Kwon, O., Choi, M.B., 2019. Quantitative analysis of research topics and public concern on V. velutina as invasive species in Asian and European countries. Entomological Research 49, 456-461.
• Dragović, N., Vasiljević, Ð., Stankov, U., Vujičić, M., 2019. Go social for your own safety! Review of social networks use on natural disasters – case studies from worldwide. Open Geosciences 11, 352-366.
• Fernández-Bellon D, Kane A. Natural history films raise species awareness—A big data approach. Conservation Letters e12678.
• Fisher, D.M., Wood, S.A., Roh, Y.-H., Kim, C.-K., 2019. The Geographic Spread and Preferences of Tourists Revealed by User-Generated Information on Jeju Island, South Korea. Land 8, 73.
• Fukano, Y., Soga, M., 2019. Spatio-temporal dynamics and drivers of public interest in invasive alien species. Biological Invasions 21, 3521-3532.
• Ghermandi, A., Camacho-Valdez, V., 2019. Mapping the cultural services of ecosystems and heritage sites in the Usumacinta floodplain in Mexico. pp 104-120, in Mainstreaming Natural Capital and Ecosystem Services into Development Policy, Kumar P. ed.
• Ghermandi, A., Sinclair, M., 2019. Passive crowdsourcing of social media in environmental research: A systematic map. Global Environmental Change 55, 36-47.
• Gosal AS, Geijzendorffer IR, Václavík T, Poulin B, Ziv G. 2019. Using social media, machine learning and natural language processing to map multiple recreational beneficiaries. Ecosystem Services 38:100958.
• Hale, R.L., Cook, E.M., Beltrán, B.J., 2019. Cultural ecosystem services provided by rivers across diverse social-ecological landscapes: A social media analysis. Ecological Indicators 107, 105580.
• Hausmann, A., Toivonen, T., Fink, C., Heikinheimo, V., Tenkanen, H., Butchart, S.H.M., Brooks, T.M., Di Minin, E., 2019. Assessing global popularity and threats to Important Bird and Biodiversity Areas using social media data. Science of the Total Environment 683, 617-623.
• Heinrich, S., Ross, J.V., Cassey, P., 2019. Of cowboys, fish, and pangolins: US trade in exotic leather. Conservation Science and Practice 1, e75.
• Jarić, I., R. A. Correia, D. L. Roberts, J. Gessner, Y. Meinard, and F. Courchamp. 2019. On the overlap between scientific and societal taxonomic attentions - Insights for conservation. Science of the Total Environment 648:772-778.
• Jensen, T.J., Auliya, M., Burgess, N.D., Aust, P.W., Pertoldi, C., Strand, J., 2019. Exploring the international trade in African snakes not listed on CITES: highlighting the role of the internet and social media. Biodiversity and Conservation 28, 1-19.
• Kim, Y., Kim, C.-k., Lee, D.K., Lee, H.-w., Andrada, R.I.I.T., 2019. Quantifying nature-based tourism in protected areas in developing countries by using social big data. Tourism Management 72, 249-256.
• Jiménez-Alvarado D, Sarmiento-Lezcano A, Guerra-Marrero A, Tuya F, Santana Del Pino Á, Sealey MJ, Castro JJ. Historical photographs of captures of recreational fishers indicate overexploitation of nearshore resources at an oceanic island. Journal of Fish Biology. pp 104-120, in Mainstreaming Natural Capital and Ecosystem Services into Development Policy
• Kang, Y., Jia, Q., Gao, S., Zeng, X., Wang, Y., Angsuesser, S., Liu, Y., Ye, X., Fei, T., 2019. Extracting human emotions at different places based on facial expressions and spatial clustering analysis. Transactions in GIS 23, 450-480.
• Kaufmann, M., Siegfried, P., Huck, L., Stettler, J., 2019. Analysis of Tourism Hotspot Behaviour Based on Geolocated Travel Blog Data: The Case of Qyer. ISPRS International Journal of Geo-Information 8, 493.
• Koylu C, Zhao C, Shao W. 2019. Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr. ISPRS International Journal of Geo-Information 8:45.
• Ladle RJ, Jepson P, Correia RA, Malhado ACM. A culturomics approach to quantifying the salience of species on the global internet. People and Nature 1:524-532.
• Lee, H., Seo, B., Koellner, T., Lautenbach, S., 2019. Mapping cultural ecosystem services 2.0 – Potential and shortcomings from unlabeled crowd sourced images. Ecological Indicators 96:505-515.
• Lennox RJ, Veríssimo D, Twardek WM, Davis CR, Jarić I. Sentiment analysis as a measure of conservation culture in scientific literature. Conservation Biology 34:462-471.
• Lioy, S., Marsan, A., Balduzzi, A., Wauters, L.A., Martinoli, A., Bertolino, S., 2019. The management of the introduced grey squirrel seen through the eyes of the media. Biological Invasions 21:3723-3733.
• Lopez, B.E., Magliocca, N.R., Crooks, A.T., 2019. Challenges and Opportunities of Social Media Data for Socio-Environmental Systems Research. Land 8, 107.
• Lyu, F., Zhang, L., 2019. Using multi-source big data to understand the factors affecting urban park use in Wuhan. Urban Forestry & Urban Greening 43, 126367.
• McClain, C.R., 2019. Likes, comments, and shares of marine organism imagery on Facebook. PeerJ 7, e6795.
• Measey, J., Basson, A., Rebelo, A.D., Nunes, A.L., Vimercati, G., Louw, M., Mohanty, N.P., 2019. Why Have a Pet Amphibian? Insights From YouTube. Frontiers in Ecology and Evolution 7.
• Mittermeier, J. C., U. Roll, T. J. Matthews, T.J, R. Grenyer. 2019. A season for all things: phenological imprints in Wikipedia usage and their relevance to conservation. PLoS biology 17:e3000146.
• Norman, P., Pickering, C.M., Castley, G., 2019. What can volunteered geographic information tell us about the different ways mountain bikers, runners and walkers use urban reserves? Landscape and Urban Planning 185, 180-190.
• Pierdicca, R., Paolanti, M., Vaira, R., Marcheggiani, E., Malinverni, E.S., Frontoni, E., 2019. Identifying the use of a park based on clusters of visitors' movements from mobile phone data. Journal of Spatial Information Science, 29-52.
• Retka, J., Jepson, P., Ladle, R.J., Malhado, A.C.M., Vieira, F.A.S., Normande, I.C., Souza, C.N., Bragagnolo, C., Correia, R.A., 2019. Assessing cultural ecosystem services of a large marine protected area through social media photographs. Ocean & Coastal Management 176: 40-48.
• Rossi, S.D., Barros, A., Walden-Schreiner, C., Pickering, C., 2019. Using social media images to assess ecosystem services in a remote protected area in the Argentinean Andes. Ambio, 1-15.
• Schuetz J. G. and A. Johnston Characterizing the cultural niches of North American birds. PNAS 116: 10868-10873.
• Schwartz, A.J., Dodds, P.S., O'Neil-Dunne, J.P.M., Danforth, C.M., Ricketts, T.H., 2019. Visitors to urban greenspace have higher sentiment and lower negativity on Twitter. People and Nature 1, 476-485.
• Sim, J., Miller, P., 2019. Understanding an urban park through big data. International Journal of Environmental Research and Public Health 16, 3816.
• Sinclair, M., Ghermandi, A., Moses, S.A., Joseph, S., 2019. Recreation and environmental quality of tropical wetlands: A social media based spatial analysis. Tourism Management 71, 179-186.
• Soulsbury, C.D., 2020. Temporal patterns of human-fox interactions as revealed from internet searches. Human Dimensions of Wildlife 25, 70-81.
• Spalding M, Parrett CL. 2019. Global patterns in mangrove recreation and tourism. Marine Policy, 103540.
• Spee LB, Hazel SJ, Dal Grande E, Boardman WSJ, Chaber A-L. 2019. Endangered Exotic Pets on Social Media in the Middle East: Presence and Impact. Animals 9:480.
• Toivonen, T., V. Heikinheimo, C. Fink, A. Hausmann, T. Hiippala, O. Järv, H. Tenkanen, and E. Di Minin. 2019. Social media data for conservation science: A methodological overview. Biological Conservation 233:298-315.
• Troumbis, A.Y., 2019. The time and timing components of conservation culturomics cycles and scenarios of public interest in the Google era. Biodiversity and Conservation 28: 1717-1727.
• Veríssimo D, Anderson S, Tlusty M. 2020. Did the movie Finding Dory increase demand for blue tang fish? Ambio 49:903-911.
• Walker, O., Simpson, G.D., Teo, A.C., Newsome, D., 2019. Preprint: Crowdsourcing and Analysing Wildlife Tourism Data from Photographs Shared on Social Media. Preprint.
• Wartmann, F.M., Tieskens, K.F., van Zanten, B.T., Verburg, P.H., 2019. Exploring tranquillity experienced in landscapes based on social media. Applied Geography 113, 102112.
• Wyckhuys KAG, Pozsgai G, Lovei GL, Vasseur L, Wratten SD, Gurr GM, Reynolds OL, Goettel M. 2019. Global disparity in public awareness of the biological control potential of invertebrates. Science of The Total Environment 660:799-806.
• Xu, Q., Li, J., Cai, M., Mackey, T.K., 2019. Use of Machine Learning to Detect Wildlife Product Promotion and Sales on Twitter. Frontiers in Big Data 2.
• Zamora, A., 2019. Making Room for Big Data: Web Scraping and an Affirmative Right to Access Publicly Available Information Online. J. Bus. Entrepreneurship & L. 12, 203.

 
2018

• Angradi, T.R., Launspach, J.J., Debbout, R., 2018. Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media. Journal of Great Lakes Research 44, 340-351.
• Archibald, C. L., and N. Butt. 2018. Using Google search data to inform global climate change adaptation policy. Climatic Change 150:447-456.
• Braczkowski A, et al. 2018. Reach and messages of the world's largest ivory burn. Conservation Biology 32:765-773.
• Burivalova, Z., R. A. Butler, and D. S. Wilcove. 2018. Analyzing Google search data to debunk myths about the public's interest in conservation. Frontiers in Ecology and the Environment 16:509-514
• Byczek, C., Longaretti, P.-Y., Renaud, J., Lavorel, S., 2018. Benefits of crowd-sourced GPS information for modelling the recreation ecosystem service. PLoS ONE 13, e0202645.
• Chamberlain J. 2018. Chapter Five - Using Social Media for Biomonitoring: How Facebook, Twitter, Flickr and Other Social Networking Platforms Can Provide Large-Scale Biodiversity Data. Pages 133-168 in Bohan DA, Dumbrell AJ, Woodward G, and Jackson M, editors. Advances in Ecological Research. Academic Press.
• Chen Y, Parkins JR, Sherren K. 2018. Using geo-tagged Instagram posts to reveal landscape values around current and proposed hydroelectric dams and their reservoirs. Landscape and Urban Planning 170:283-292.
• Correia, R. A., Z. C. Correia, A. C. Malhado, and R. J. Ladle. 2018. Pivotal 20th century contributions to the development of the Anthropocene concept: overview and implications. Current Science 115:1871.
• Correia, R. A., I. Jarić, P. Jepson, A. C. Malhado, J. A. Alves, and R. J. Ladle. 2018. Nomenclature instability in species culturomic assessments: Why synonyms matter. Ecological Indicators 90:74-78.
• Correia, R. A., P. Jepson, A. C. M. Malhado, and R. J. Ladle. 2018. Culturomic assessment of Brazilian protected areas: Exploring a novel index of protected area visibility. Ecological Indicators 85:165-171.
• Courchamp, F., I. Jaric, C. Albert, Y. Meinard, W. J. Ripple, and G. Chapron. 2018. The paradoxical extinction of the most charismatic animals. PLoS Biology 16:e2003997.
• Davies T, et al. 2018. Popular interest in vertebrates does not reflect extinction risk and is associated with bias in conservation investment. PLoS ONE 13:e0203694.
• Di Minin, E., C. Fink, T. Hiippala, and H. Tenkanen. 2018. A framework for investigating illegal wildlife trade on social media with machine learning. Conservation Biology 33:210-213.
• Di Minin, E., C. Fink, H. Tenkanen, and T. Hiippala. 2018. Machine learning for tracking illegal wildlife trade on social media. Nature Ecology & Evolution 2:406-407.
• Donahue, M.L., Keeler, B.L., Wood, S.A., Fisher, D.M., Hamstead, Z.A., McPhearson, T., 2018. Using social media to understand drivers of urban park visitation in the Twin Cities, MN. Landscape and Urban Planning 175, 1-10.
• Fisher, D.M., Wood, S.A., White, E.M., Blahna, D.J., Lange, S., Weinberg, A., Tomco, M., Lia, E., 2018. Recreational use in dispersed public lands measured using social media data and on-site counts. Journal of Environmental Management 222, 465-474.
• Ghermandi A. 2018. Integrating social media analysis and revealed preference methods to value the recreation services of ecologically engineered wetlands. Ecosystem Services 31:351-357.
• Giovos I, et al. 2018. Identifying recreational fisheries in the Mediterranean Sea through social media. Fisheries Management and Ecology 25:287-295.
• Haider, C.M.R., Ali, M.E., 2018. Can We Predict the Scenic Beauty of Locations from Geo-tagged Flickr Images?, In International Conference on Intelligent User Interfaces (IUI). pp. 653-657, Tokyo, Japan.
• Hale, B.W., 2018. Mapping Potential Environmental Impacts from Tourists Using Data from Social Media: A Case Study in the Westfjords of Iceland. Environmental Management 62, 446-457.
• Hamstead, Z.A., Fisher, D., Ilieva, R.T., Wood, S.A., McPhearson, T., Kremer, P., 2018. Geolocated social media as a rapid indicator of park visitation and equitable park access. Computers, Environment and Urban Systems 72, 38-50.
• Hausmann, A., T. Toivonen, R. Slotow, H. Tenkanen, A. Moilanen, V. Heikinheimo, and E. Di Minin. 2018. Social Media Data Can Be Used to Understand Tourists' Preferences for Nature-Based Experiences in Protected Areas. Conservation Letters 11:e12343.
• Hiippala, T., A. Hausmann, H. Tenkanen, and T. Toivonen. 2018. Exploring the linguistic landscape of geotagged social media content in urban environments. Digital Scholarship in the Humanities 34:290–309.
• Kidd LR, Gregg EA, Bekessy SA, Robinson JA, Garrard GE. 2018. Tweeting for their lives: Visibility of threatened species on twitter. Journal for Nature Conservation 46:106-109.
• Kim JY, Noda A, Im R-Y, Nishihiro J. 2018. Web search volume as a surrogate of public interest in biodiversity: a case study of Japanese red list species. Ecosystem Health and Sustainability 4:289-298.
• Koylu C, Zhao C, Shao W. 2019. Deep Neural Networks and Kernel Density Estimation for Detecting Human Activity Patterns from Geo-Tagged Images: A Case Study of Birdwatching on Flickr. ISPRS International Journal of Geo-Information 8:45.
• Legagneux, P., N. Casajus, K. Cazelles, C. Chevallier, M. Chevrinais, L. Guéry, C. Jacquet, M. Jaffré, M.-J. Naud, F. Noisette, P. Ropars, S. Vissault, P. Archambault, J. Bêty, D. Berteaux, and D. Gravel. 2018. Our House Is Burning: Discrepancy in Climate Change vs. Biodiversity Coverage in the Media as Compared to Scientific Literature. Frontiers in Ecology and Evolution 5:175.
• Lotan, A., Kost, R., Mandelik, Y., Peled, Y., Chakuki , D., Zemah Shamir, S., Ram, Y., 2018. National scale mapping of ecosystem services in Israel – genetic resources, pollination and cultural services. One Ecosystem 3.
• Mancini, F., Coghill, G.M., Lusseau, D., 2018. Using social media to quantify spatial and temporal dynamics of nature-based recreational activities. PLoS ONE 13, e0200565.
• Martinez-Harms, M.J., Bryan, B.A., Wood, S.A., Fisher, D.M., Law, E., Rhodes, J.R., Dobbs, C., Biggs, D., Wilson, K.A., 2018. Inequality in access to cultural ecosystem services from protected areas in the Chilean biodiversity hotspot. Science of the Total Environment 636, 1128-1138.
• Mikula P, Hadrava J, Albrecht T, Tryjanowski P. 2018. Large-scale assessment of commensalistic-mutualistic associations between African birds and herbivorous mammals using internet photos. PeerJ 6:e4520.
• Monkman, G. G., M. J. Kaiser, and K. Hyder. 2018. Text and data mining of social media to map wildlife recreation activity. Biological Conservation 228:89-99.
• Richards DR, Tunçer B. 2018. Using image recognition to automate assessment of cultural ecosystem services from social media photographs. Ecosystem Services 31:318-325.
• Roll, U., R. A. Correia, and O. Berger-Tal. 2018. Using machine learning to disentangle homonyms in large text corpora. Conservation Biology 32:716-724.
• Seresinhe CI, Moat HS, Preis T. 2018. Quantifying scenic areas using crowdsourced data. Environment and Planning B: Urban Analytics and City Science 45:567-582.
• Silk MJ, Crowley SL, Woodhead AJ, Nuno A. 2018. Considering connections between Hollywood and biodiversity conservation. Conservation Biology 32:597-606.
• Sinclair M, Ghermandi A, Sheela AM. 2018. A crowdsourced valuation of recreational ecosystem services using social media data: An application to a tropical wetland in India. The Science of the total environment 642:356-365.
• Sung, Y.-H., Fong, J.J., 2018. Assessing consumer trends and illegal activity by monitoring the online wildlife trade. Biological Conservation 227, 219-225.
• Svoray, T., Dorman, M., Shahar, G., Kloog, I., 2018. Demonstrating the effect of exposure to nature on happy facial expressions via Flickr data: Advantages of non-intrusive social network data analyses and geoinformatics methodologies. Journal of Environmental Psychology 58, 93-100.
• Van Berkel, D.B., Tabrizian, P., Dorning, M.A., Smart, L., Newcomb, D., Mehaffey, M., Neale, A., Meentemeyer, R.K., 2018. Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR. Ecosystem Services 31, 326-335.
• Veríssimo, D., A. Bianchessi, A. Arrivillaga, F. C. Cadiz, R. Mancao, and K. Green. 2018. Does it work for biodiversity? Experiences and challenges in the evaluation of social marketing campaigns. Social Marketing Quarterly 24:18-34.
• Vieira, F. A., C. Bragagnolo, R. A. Correia, A. C. Malhado, and R. J. Ladle. 2018. A salience index for integrating multiple user perspectives in cultural ecosystem service assessments. Ecosystem Services 32:182-192.
• Wäldchen, J., Mäder, P., 2018. Machine learning for image based species identification. Methods in Ecology and Evolution 9, 2216-2225.
• Wäldchen J, Rzanny M, Seeland M, Mäder P. 2018. Automated plant species identification—Trends and future directions. PLOS Computational Biology 14:e1005993.
• Walden-Schreiner, C., Rossi, S.D., Barros, A., Pickering, C., Leung, Y.-F., 2018. Using crowd-sourced photos to assess seasonal patterns of visitor use in mountain-protected areas. Ambio 47, 781-793.
• Walden-Schreiner, C., Leung, Y.-F., Tateosian, L., 2018. Digital footprints: Incorporating crowdsourced geographic information for protected area management. Applied Geography 90, 44-54.
• Wang, Z., Jin, Y., Liu, Y., Li, D., Zhang, B., 2018. Comparing social media data and survey data in assessing the attractiveness of Beijing Olympic Forest Park. Sustainability 10, 382.
• Zhang, S., Zhou, W., 2018. Recreational visits to urban parks and factors affecting park visits: Evidence from geotagged social media data. Landscape and Urban Planning 180, 27-35.

 
2017

• Becken S, Stantic B, Chen J, Alaei AR, Connolly RM. 2017. Monitoring the environment and human sentiment on the Great Barrier Reef: Assessing the potential of collective sensing. Journal of Environmental Management 203:87-97.
• Colléony, A., Clayton, S., Couvet, D., Saint Jalme, M., Prévot, A.-C., 2017. Human preferences for species conservation: Animal charisma trumps endangered status. Biological Conservation 206, 263-269.
• Correia, R. A., P. Jepson, A. C. M. Malhado, and R. J. Ladle. 2017. Internet scientific name frequency as an indicator of cultural salience of biodiversity. Ecological Indicators 78:549-555.
• Hausmann, A., T. Toivonen, V. Heikinheimo, H. Tenkanen, R. Slotow, and E. Di Minin. 2017. Social media reveal that charismatic species are not the main attractor of ecotourists to sub-Saharan protected areas. Scientific Reports 7:763.
• Heikinheimo, V., E. D. Minin, H. Tenkanen, A. Hausmann, J. Erkkonen, and T. Toivonen. 2017. User-generated geographic information for visitor monitoring in a national park: A comparison of social media data and visitor survey. ISPRS International Journal of Geo-Information 6:85.
• Hong S, Do Y, Kim JY, Cowan P, Joo G-J. 2017. Conservation activities for the Eurasian otter (Lutra lutra) in South Korea traced from newspapers during 1962–2010. Biological Conservation 210:157-162.
• Kesebir S, Kesebir P. 2017. A Growing Disconnection From Nature Is Evident in Cultural Products. Perspectives on Psychological Science 12:258-269.
• Korpilo, S., Virtanen, T., Lehvävirta, S., 2017. Smartphone GPS tracking—Inexpensive and efficient data collection on recreational movement. Landscape and Urban Planning 157, 608-617.
• Kusmanoff, A. M., F. Fidler, A. Gordon, and S. A. Bekessy. 2017. Decline of 'biodiversity' in conservation policy discourse in Australia. Environmental Science & Policy 77:160-165.
• Ladle, R. J., P. Jepson, R. A. Correia, and A. C. Malhado. 2017. The power and the promise of culturomics. Frontiers in Ecology and the Environment 15:290-291.
• Levin, N., Lechner, A.M., Brown, G., 2017. An evaluation of crowdsourced information for assessing the visitation and perceived importance of protected areas. Applied Geography 79, 115-126.
• Megias, D. A., S. C. Anderson, R. J. Smith, and D. Veríssimo. 2017. Investigating the impact of media on demand for wildlife: A case study of Harry Potter and the UK trade in owls. PLoS ONE 12:e0182368.
• Norman, P., Pickering, C.M., 2017. Using volunteered geographic information to assess park visitation: Comparing three on-line platforms. Applied Geography 89, 163-172.
• Oteros-Rozas E, Martín-López B, Fagerholm N, Bieling C, Plieninger T. 2018. Using social media photos to explore the relation between cultural ecosystem services and landscape features across five European sites. Ecological Indicators 94:74-86.
• Seresinhe CI, Preis T, Moat HS. 2017. Using deep learning to quantify the beauty of outdoor places. Royal Society Open Science 4:170170.
• Sherren K, Parkins JR, Smit M, Holmlund M, Chen Y. 2017. Digital archives, big data and image-based culturomics for social impact assessment: Opportunities and challenges. Environmental Impact Assessment Review 67:23-30.
• Sherren, K., Smit, M., Holmlund, M., Parkins, J.R., Chen, Y., 2017. Conservation culturomics should include images and a wider range of scholars. Frontiers in Ecology and the Environment 15, 289-290.
• Soriano-Redondo A, Bearhop S, Lock L, Votier SC, Hilton GM. 2017. Internet-based monitoring of public perception of conservation. Biological Conservation 206:304-309.
• Stergiou K. 2017. The most famous fish: Human relationships with fish as inferred from the corpus of online English books (1800-2000). Ethics in Science and Environmental Politics 17:9-18.
• Tandoc, E.C., Eng, N., 2017. Climate Change Communication on Facebook, Twitter, Sina Weibo, and Other Social Media Platforms. Oxford University Press.
• Tenkanen, H., E. Di Minin, V. Heikinheimo, A. Hausmann, M. Herbst, L. Kajala, and T. Toivonen. 2017. Instagram, Flickr, or Twitter: Assessing the usability of social media data for visitor monitoring in protected areas. Scientific Reports 7:17615.
• Thaler, A.D., Rose, N.A., Cosentino, A.M., Wright, A.J., 2017. Lions, Whales, and the Web: Transforming Moment Inertia into Conservation Action. Frontiers in Marine Science 4.
• Troumbis, A. Y. 2017. Declining Google Trends of public interest in biodiversity: semantics, statistics or traceability of changing priorities? Biodiversity and Conservation 26:1495-1505.
• Troumbis AY. 2017. Google Trends and cycles of public interest in biodiversity: the animal spirits effect. Biodiversity and Conservation 26:3421-3443.
• Veríssimo, D., G. Vaughan, M. Ridout, C. Waterman, D. MacMillan, and R. J. Smith. 2017. Increased conservation marketing effort has major fundraising benefits for even the least popular species. Biological Conservation 211, Part A:95-101.
• Wu, X., Wood, S.A., Fisher, D., Lindsey, G., 2017. Photos, tweets, and trails: Are social media proxies for urban trail use? Journal of Transport and Land Use 10.
• Zook, M. et al. 2017. Ten simple rules for responsible big data research. PLoS Computational Biology 13, e1005399.

 
2016

• Andrew, L., Arndt, D., Beristain, N., Cass, T., Clow, T., Colmenares, B., Damm, K., Hatcher, R., Jackson, N., Pasquesi, W., 2016. Changes in United States’ citizens’ interest in sustainability (2004–2014). Life: The Excitement of Biology 4, 138-164.
• Correia, R. A., P. R. Jepson, A. C. M. Malhado, and R. J. Ladle. 2016. Familiarity breeds content: assessing bird species popularity with culturomics. PeerJ 4:e1728.
• Daume S, Galaz V. 2016. “Anyone Know What Species This Is?” – Twitter Conversations as Embryonic Citizen Science Communities. PLoS One 11:e0151387.
• Ghermandi A. 2016. Analysis of intensity and spatial patterns of public use in natural treatment systems using geotagged photos from social media. Water Research 105:297-304.
• Giovos, I., Ganias, K., Garagouni, M., Gonzalvo, J., 2016. Social media in the service of conservation: A case study of dolphins in the Hellenic seas. Aquatic Mammals 42, 12-20.
• Gliozzo, G., Pettorelli, N., Haklay, M., 2016. Using crowdsourced imagery to detect cultural ecosystem services: a case study in South Wales, UK. Ecology and Society 21.
• Hentati-Sundberg J, Olsson O. 2016. Amateur photographs reveal population history of a colonial seabird. Current Biology 26:R226-R228.
• Hinsley A, Lee TE, Harrison JR, Roberts DL. 2016. Estimating the extent and structure of trade in horticultural orchids via social media. Conservation Biology 30:1038-1047.
• Jarić, I., F. Courchamp, J. Gessner, and D. L. Roberts. 2016. Data mining in conservation research using Latin and vernacular species names. PeerJ 4:e2202.
• Jiang H, Lin P, Qiang M. 2016. Public-Opinion Sentiment Analysis for Large Hydro Projects. Journal of Construction Engineering and Management 142:05015013.
• Ladle, R. J., R. A. Correia, Y. Do, G.-J. Joo, A. Malhado, R. Proulx, J.-M. Roberge, and P. Jepson. 2016. Conservation culturomics. Frontiers in Ecology and the Environment 14:269-275.
• Leighton GRM, Hugo PS, Roulin A, Amar A. 2016. Just Google it: assessing the use of Google Images to describe geographical variation in visible traits of organisms. Methods in Ecology and Evolution 7:1060-1070.
• Miranda EBP, Ribeiro RP, Strüssmann C. 2016. The Ecology of Human-Anaconda Conflict: A Study Using Internet Videos. Tropical Conservation Science 9:43-77.
• Nechanska D, Kurikova P, Patoka J, Kalous L. 2016. Does recreational fisheries contribute to spreading of pumpkinseed (Lepomis gibbosus L.) in the Czech Republic? MendelNet 2016:343-346.
• Nghiem, L. T. P., S. K. Papworth, F. K. S. Lim, and L. R. Carrasco. 2016. Analysis of the Capacity of Google Trends to Measure Interest in Conservation Topics and the Role of Online News. PLoS One 11:e0152802.
• Nunez-Mir, G. C., B. V. Iannone, B. C. Pijanowski, N. Kong, and S. Fei. 2016. Automated content analysis: addressing the big literature challenge in ecology and evolution. Methods in Ecology and Evolution 7:1262-1272.
• Roll, U., J. C. Mittermeier, G. I. Diaz, M. Novosolov, A. Feldman, Y. Itescu, S. Meiri, and R. Grenyer. 2016. Using Wikipedia page views to explore the cultural importance of global reptiles. Biological Conservation 204, Part A:42-50.
• Sessions, C., Wood, S.A., Rabotyagov, S., Fisher, D.M., 2016. Measuring recreational visitation at U.S. National Parks with crowd-sourced photographs. Journal of Environmental Management 183, 703-711.
• Sonter LJ, Watson KB, Wood SA, Ricketts TH. 2016. Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media. PLoS One 11:e0162372.
• Sula, C.A., 2016. Research Ethics in an Age of Big Data. Bulletin of the Association for Information Science and Technology 42, 17-21.
• Zablocki J, Arora S, Barua M. 2016. Factors affecting media coverage of species rediscoveries. Conservation Biology 30:914-917.

 
2015

• Arts K, van der Wal R, Adams WM. 2015. Digital technology and the conservation of nature. Ambio 44:661-673.
• Carter DW, Crosson S, Liese C. 2015. Nowcasting Intraseasonal Recreational Fishing Harvest with Internet Search Volume. PLoS One 10:e0137752.
• Di Minin, E., H. Tenkanen, and T. Toivonen. 2015. Prospects and challenges for social media data in conservation science. Frontiers in Environmental Science 3.
• Do Y, Kim JY, Lineman M, Kim D-K, Joo G-J. 2015. Using internet search behavior to assess public awareness of protected wetlands. Conservation Biology 29:271-279.
• El Bizri HR, Morcatty T, Q., Lima J, J. S., Valsecchi J. 2015. The thrill of the chase: uncovering illegal sport hunting in Brazil through YouTube posts. Ecology and Society 20:30.
• Haas AF, et al. 2015. Can we measure beauty? Computational evaluation of coral reef aesthetics. PeerJ 3:e1390.
• Humair, F., Humair, L., Kuhn, F., Kueffer, C., 2015. E-commerce trade in invasive plants. Conservation Biology 29, 1658-1665.
• Jang, S.M., Hart, P.S., 2015. Polarized frames on “climate change” and “global warming” across countries and states: Evidence from Twitter big data. Global Environmental Change 32, 11-17.
• Jepson, P., and R. J. Ladle. 2015. Nature apps: Waiting for the revolution. Ambio 44:827-832.
• Levin N, Kark S, Crandall D. 2015. Where have all the people gone? Enhancing global conservation using night lights and social media. Ecological Applications 25:2153-2167.
• Lineman, M., Y. Do, J. Y. Kim, and G.-J. Joo. 2015. Talking about Climate Change and Global Warming. PLoS One 10:e0138996.
• Moorhouse TP, Dahlsjö CAL, Baker SE, D'Cruze NC, Macdonald DW. 2015. The Customer Isn't Always Right—Conservation and Animal Welfare Implications of the Increasing Demand for Wildlife Tourism. PLoS One 10:e0138939.
• Papworth, S. K., T. P. L. Nghiem, D. Chimalakonda, M. R. C. Posa, L. S. Wijedasa, D. Bickford, and L. R. Carrasco. 2015. Quantifying the role of online news in linking conservation research to Facebook and Twitter. Conservation Biology 29:825-833.
• Richards DR, Friess DA. 2015. A rapid indicator of cultural ecosystem service usage at a fine spatial scale: Content analysis of social media photographs. Ecological Indicators 53:187-195.
• Schuetz, J., Soykan, C.U., Distler, T., Langham, G., 2015. Searching for backyard birds in virtual worlds: Internet queries mirror real species distributions. Biodiversity and Conservation 24, 1147-1154.

 
2014

• Anderegg WRL, Goldsmith GR. 2014. Public interest in climate change over the past decade and the effects of the ‘climategate’ media event. Environmental Research Letters 9:054005.
• Cody, E.M., Reagan, A.J., Mitchell, L., Dodds, P.S., Danforth, C.M., 2015. Climate Change Sentiment on Twitter: An Unsolicited Public Opinion Poll. PLoS ONE 10, e0136092.
• Funk SM, Rusowsky D. 2014. The importance of cultural knowledge and scale for analysing internet search data as a proxy for public interest toward the environment. Biodiversity and Conservation 23:3101-3112.
• Kim JY, Do Y, Im R-Y, Kim G-Y, Joo G-J. 2014. Use of large web-based data to identify public interest and trends related to endangered species. Biodiversity and Conservation 23:2961-2984.
• Kirilenko, A.P., Stepchenkova, S.O., 2014. Public microblogging on climate change: One year of Twitter worldwide. Global Environmental Change 26, 171-182.
• Martin DR, Chizinski CJ, Eskridge KM, Pope KL. 2014. Using posts to an online social network to assess fishing effort. Fisheries Research 157:24-27.
• Proulx, R., P. Massicotte, and M. Pepino. 2014. Googling Trends in Conservation Biology. Conservation Biology 28:44-51.
• Roberge J-M. 2014. Using data from online social networks in conservation science: which species engage people the most on Twitter? Biodiversity and Conservation 23:715-726.
• Veríssimo, D., D. C. MacMillan, R. J. Smith, J. Crees, and Z. G. Davies. 2014. Has climate change taken prominence over biodiversity conservation? Bioscience 64:625-629.

2013

• Brambilla, M., Gustin, M., Celada, C., 2013. Species appeal predicts conservation status. Biological Conservation 160, 209-213.
• Casalegno S, Inger R, DeSilvey C, Gaston KJ. 2013. Spatial Covariance between Aesthetic Value & Other Ecosystem Services. PLoS One8:e68437.
• Clements CF. 2013. Public interest in the extinction of a species may lead to an increase in donations to a large conservation charity. Biodiversity and Conservation 22:2695-2699.
• Ficetola GF. 2013. Is interest toward the environment really declining? The complexity of analysing trends using internet search data. Biodiversity and Conservation 22:2983-2988.
• Kádár, B., Gede, M., 2013. Where do tourists go? Visualizing and analysing the spatial distribution of geotagged photography. Cartographica: The international journal for geographic information and geovisualization 48, 78-88.
• Mccallum ML, Bury GW. 2013. Google search patterns suggest declining interest in the environment. Biodiversity and Conservation 22:1355-1367.
• Orsi F, Geneletti D. 2013. Using geotagged photographs and GIS analysis to estimate visitor flows in natural areas. Journal for Nature Conservation 21:359-368.
• Richards DR. 2013. The content of historical books as an indicator of past interest in environmental issues. Biodiversity and Conservation 22:2795-2803.
• Wilde GR, Pope KL. 2013. Worldwide trends in fishing interest indicated by internet search volume. Fisheries Management and Ecology 20:211-222.
• Wood, S.A., Guerry, A.D., Silver, J.M., Lacayo, M., 2013. Using social media to quantify nature-based tourism and recreation. Scientific Reports 3, 2976.
• Zielstra, D., Hochmair, H.H., 2013. Positional accuracy analysis of Flickr and Panoramio images for selected world regions. Journal of Spatial Science 58, 251-273.
• Żmihorski M, Dziarska-Pałac J, Sparks TH, Tryjanowski P. 2013. Ecological correlates of the popularity of birds and butterflies in Internet information resources. Oikos 122:183-190.

2012

• Bosch, T., 2012. Blogging and tweeting climate change in South Africa. Ecquid Novi: African Journalism Studies 33, 44-53.
• Crandall, D., Snavely, N., 2012. Modeling people and places with internet photo collections. Commun. ACM 55, 52–60.
• Elwood, S., Goodchild, M.F., Sui, D.Z., 2012. Researching Volunteered Geographic Information: Spatial Data, Geographic Research, and New Social Practice. Annals of the Association of American Geographers 102, 571-590.
• Kikillus, K.H., Hare, K.M., Hartley, S., 2012. Online trading tools as a method of estimating propagule pressure via the pet-release pathway. Biological Invasions 14, 2657-2664.
• Martin DR, Pracheil BM, DeBoer JA, Wilde GR, Pope KL. 2012. Using the Internet to Understand Angler Behavior in the Information Age. Fisheries 37:458-463.
• Sonricker Hansen, A.L., Li, A., Joly, D., Mekaru, S., Brownstein, J.S., 2012. Digital Surveillance: A Novel Approach to Monitoring the Illegal Wildlife Trade. PLoS ONE 7, e51156.

2010

• Clark, G.E., 2010. The Changing News Environment. Environment 52, 5-7.

2009

• Clark, G.E., 2009. Environmental twitter. Environment: Science and Policy for Sustainable Development 51, 5-7.

2008

• Elwood, S., 2008. Volunteered geographic information: key questions, concepts and methods to guide emerging research and practice. GeoJournal 72, 133-135.

2007

• Goodchild, M.F., 2007. Citizens as sensors: the world of volunteered geography. GeoJournal 69, 211-221.
• Suiter, K., Sferrazza, S., 2007. Monitoring the sale and trafficking of invasive vertebrate species using automated internet search and surveillance tools. Managing Vertebrate Invasive Species 51.
• Wilson JR, Procheş Ş, Braschler B, Dixon ES, Richardson DM. 2007. The (bio)diversity of science reflects the interests of society. Frontiers in Ecology and the Environment 5:409-414.