The Recommendation System to SNS Community for Tourists by Using Altruistic Behaviors
Takumi Ichimura, Takuya Uemoto, Shin Kamada

TL;DR
This paper presents a simulation-based recommendation system for SNS communities that uses altruistic behaviors inspired by army ants to stimulate tourist participation and community vitality.
Contribution
It introduces a novel altruistic behavior model inspired by army ants to enhance SNS community engagement for tourists.
Findings
Altruistic behaviors effectively stimulate tourist activity.
Simulation results show increased community vitality.
The method reduces selfish behaviors in SNS communities.
Abstract
We have already developed the recommendation system of sightseeing information on SNS by using smartphone based user participatory sensing system. The system can post the attractive information for tourists to the specified Facebook page by our developed smartphone application. The users in Facebook, who are interested in sightseeing, can come flocking through information space from far and near. However, the activities in the community on SNS are only supported by the specified people called a hub. We proposed the method of vitalization of tourist behaviors to give a stimulus to the people. We developed the simulation system for multi agent system with altruistic behaviors inspired by the Army Ants. The army ant takes feeding action with altruistic behaviors to suppress selfish behavior to a common object used by a plurality of users in common. In this paper, we introduced the altruism…
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