A Mirror to Human Question Asking: Analyzing the Akinator Online Question Game

Gal Sasson, Yoed N. Kenett

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Question-asking is a critical aspect of human communications. Yet, little is known about the reasons that lead people to ask questions, which questions are considered better than others, or what cognitive mechanisms allow the ability to ask informative questions. Here, we take a first step towards investigating human question-asking. We do so by an exploratory data-driven analysis of the questions asked by Akinator, a popular online game of a genie who asks questions to guess the character that the user is thinking of. We propose that the Akinator’s question-asking process may be viewed as a reflection of how humans ask questions. We conduct an exploratory data analysis to examine different strategies for the Akinator’s question-asking process, ranging from mathematical algorithms to gamification-based considerations, by analyzing complete games and individual questions. Furthermore, we use topic-modelling techniques to explore the topics of the Akinator’s inquiries and map similar questions into clusters. Overall, we find surprising aspects of the specificity and types of questions generated by the Akinator game, that may be driven by the gamification characteristics of the game. In addition, we find coherent topics that the Akinator retrieves from when generating questions. Our results highlight commonalities in the strategies for question-asking used by people and by the Akinator.

Original languageEnglish
Article number26
JournalBig Data and Cognitive Computing
Volume7
Issue number1
DOIs
StatePublished - Mar 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 by the authors.

Keywords

  • Akinator
  • BERT
  • LDA
  • question asking
  • text analysis
  • topic-modelling

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