Using Social Media Photographs to Analyze Tourists’ Risky Behaviors

Authors: Yun Liang*, Department of Tourism, Recreation and Sport Management, University of Florida, Andrei Kirilenko, Department of Tourism, Recreation and Sport Management, University of Florida, Svetlana Stepchenkova, Department of Tourism, Recreation and Sport Management, University of Florida
Topics: Tourism Geography
Keywords: Social Media, Content Analysis, Photographs, Kruger National Park
Session Type: Poster
Day: 4/6/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded

With the development of social media, people are allowed to generate, exchange or comment other users’ content, like text, tag, photographs or videos. Because of the high volume of social media data, it is regarded as a new source for research. In nature-based tourism, social media photographs are used to identify visitors’ preference and mobility patterns and to quantify tourism and recreation. Kruger National Park, one of the oldest national parks in South Africa, offers a wildlife experience for tourists, who have a chance to spot the big five, wild dog, ground hornbill, and other various animals. Surrounded Kruger National Park, there are many private parks which also provide wildlife viewing for tourists. However, continuous increasing tourists in Kruger National Park causes issues in visitor management, such as lacking enough accommodation, garbage along the road, and inappropriate behaviors of some tourists during traveling (Ferreira and Harmse 2014). Therefore, utilizing content analysis to classify travel photographs collected from Instagram, the study comparatively examines tourists’ risky behaviors in Kruger National Park and surrounded private parks. Based on the regulation of Kruger National Park, we found that it can identify tourists’ risky behaviors in parks, such as protruding arms or heads from the car, not staying in the car during the trips, drinking alcohol in public areas, and touching animals, by classifying social media photographs.

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