Testing the Acceptability of Social Support Agents in Online Communities

Abstract

This paper describes the first steps towards development and evaluation of an ‘artificial friend’, i.e., an intelligent agent that provides support via text messages in social media in order to alleviate the stress that users experience as a result of everyday problems. The agent consists of three main components: (1) a module that processes text messages based on text mining and classifies them into categories of problems, (2) a module that selects appropriate support strategies based on a validated psychological model of emotion regulation, and (3) a module that generates appropriate responses based on the output of the first two modules. The application has been tested in a pilot study involving 33 participants that were asked to interact with different variants of the agent via the social network Telegram. The results provide hints that the agent is appreciated over a baseline version that generates random support messages, but also point at some possibilities to further improve the agent.