Quantified self is a growing research area in human -- computer interaction. New techniques help users to track and optimize their daily activities. Some data is collected automatically. Others like information about nutrition have to be entered manually by the user. This process is labor -- intensive and quite often the motivation is fading over the time. In this paper, an approach is introduced to simplify food tracking. This developed procedure assimilates into daily routines. The instant messaging service called Telegram is used to propose the chatbot Nombot to the user. This bot communicates with the user and collects data about the nutrition of its chat partner. Different motivation types are considered. To evaluate the described implementation, an A/B study is conducted.
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Gräf et al. (2015) studied this question.