Whale watching in Sri Lanka: Understanding the metadata of crowd-sourced photographs on FlickrTM social media platform

Abstract

Data mining on social media platforms (Instagram™, Flickr™, and Twitter™) is rapidly increasing and application of data mining techniques has contributed to significant findings in various fields such as tourism, ecology, and politics etc. In the face of globalization and nature-based tourism is thriving in many countries, social media activity on tourism is increasing despite the socio-economical barriers. In this context, this paper attempts to understand the metadata of photographs related to whale watching in Sri Lanka in Flickr social media platform. Photographs related to whale watching was extracted and analyzed for i) photographic content ii) Geo-tags iii) Social-tags and iv) Photographers’ nationalities by using Flickr API (Application Programming Interface) and self-written python program script. Content analysis of the photographs has identified five major categories (human activity, accommodation, natural phenomena, animals and other) of photographs based on the major element present in each photograph. Mapping of geo-tagged photographs indicated that Mirissa was the hotspot for whale watching in Sri Lanka. Moreover, the present study suggests that mapping of geo-tagged photographs can be used as proxy data for whale distribution in Sri Lanka.  Analysis of social tags indicated that tags indicating whale (156), Sri Lanka (144) and Mirissa (133) were popular among the photographers. The demographic profile of the photographers indicated that the highest number of photographers (25%) from the United Kingdom followed by Sri Lanka (18.69%) and China (12.94%) interested in whale watching. Despite some of the weaknesses, this study has demonstrated that metadata of Flickr photographs can effectively be used for understanding the basic information related to whale-watching tourism in Sri Lanka.