Chatbots for News Delivery – Investigations into Intrinsic Motivation and User Engagement

Abstract

The Internet has led to an unprecedented diversity in the news delivery sector. Today’s news consumers no longer inform themselves through newspapers alone. Rather it is radio and TV and increasingly also newspaper websites, social media channels, and dedicated news apps, which give them a great choice in how to keep up with ongoing developments. In this context, much hope has recently been placed on so-called news chatbots as a novel delivery format. Yet, little is known about the suitability of these chatbots as a news medium. Hence, the work presented in this paper aimed to trigger respective investigations by focusing on intrinsic motivation to use news chatbots and the resulting user engagement. In an experimental study (n = 60) we compared a linear news delivery mode in the form of a one-way newsflash delivered by a chatbot with a conversational news delivery mode in the form of back-and-forth chatbot interactions. Results show that people feel less pressured and stressed in the conversational mode, while the linear mode had a negative effect on the intrinsic motivation to use the chatbot. Furthermore, we found that the conversational mode had a positive impact on user engagement.