Classification of multimedia SNS posts about tourist sites based on their focus toward predicting eco-friendly users

Overtourism has had a negative impact on various things at tourist sites. One of the most serious problems is environmental issues, such as littering, caused by too many visitors to tourist sites. It is important to change people's mindset to be more environmentally aware in order to improve such situation. In particular, if we can find people with comparatively high awareness about environmental issues for overtourism, we will be able to work effectively to promote eco-friendly behavior for people. However, grasping a person's awareness is inherently difficult. For this challenge, we introduce a new task, called Detecting Focus of Posts about Tourism, which is given users' posts of pictures and comment on SNSs about tourist sites, to classify them into types of their focuses based on such awareness. Once we classify such posts, we can see its result showing tendencies of users awareness and so we can discern awareness of the users for environmental issues at tourist sites. Specifically, we define four labels on focus of SNS posts about tourist sites. Based on these labels, we create an evaluation dataset. We present experimental results of the classification task with a CNN classifier for pictures or an LSTM classifier for comments, which will be baselines for the task.