Applying Text Mining to Analyze Human Question Asking in Creativity Research

Anna Wròblewska, Marceli Korbin, Yoed N. Kenett, Daniel Dan, Maria Ganzha, Marcin Paprzycki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Creativity relates to the ability to generate novel, and effective, ideas in the areas of interest. How are such creative ideas generated? One possible mechanism that supports creative ideation, and is gaining increased empirical attention, is by asking questions. Question asking is a likely cognitive mechanism that allows defining problems, facilitating creative problem solving [15]. However, much is unknown about the exact role of questions in creativity. This work presents an attempt to apply text mining methods to measure the cognitive potential of questions, taking into account, among others, (a) question type, (b) question complexity, and (c) content of the answer. This contribution summarizes the history of question mining as a part of creativity research, along with the natural language processing methods deemed useful, or helpful, in the study. Furthermore, a novel approach is proposed, implemented, and applied to five datasets. Obtained experimental results are comprehensively analyzed, suggesting that natural language processing has a role to play in the creativity research.

Original languageEnglish
Title of host publicationBig Data Analytics in Astronomy, Science, and Engineering - 12th International Conference on Big Data Analytics, BDA 2024, Proceedings
EditorsShelly Sachdeva, Yutaka Watanobe, Subhash Bhalla
Pages44-73
Number of pages30
DOIs
StatePublished - 2025
Event12th International Conference on Big Data Analytics, BDA 2024 - Aizu, Japan
Duration: 26 Nov 202428 Nov 2024

Publication series

NameLecture Notes in Computer Science
Volume15546 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Big Data Analytics, BDA 2024
Country/TerritoryJapan
CityAizu
Period26/11/2428/11/24

Keywords

  • Creativity
  • Measuring questions
  • Natural language processing
  • Question asking

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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