Bibliometric Analysis of Chatbots in Health-Trend Shifts and Advancements in Artificial Intelligence for Personalized Conversational Agents

Abstract

Bibliometric analysis provides a summary for research reported in scientific literature. This can highlight pattens and trends in academic research areas, and assist in research directions. Recent growing requirements for efficient communications and increased user learning needs in the health domain, has instigated mass exploitation of chatbots. 2148 documents were analysed to show a shift in research focus around the year 2016. The rate of documents produced in the last few years is more than the collective 20 year period, and future outputs may soar. The emergence of machine and deep learning technology with chatbot usage suggested research opportunity to be exploited in techniques which embed advanced AI abilities. Key authors still spearhead the research direction but a new wave of outputs will further disperse topics into advanced techniques such as personalised disease detections and sophisticated interface that significantly mask any artificiality to their composition.