A Survey Forest Diagram : Gain a Divergent Insight View on a Specific Research Topic
Jinghong Li, Wen Gu, Koichi Ota, Shinobu Hasegawa

TL;DR
This paper introduces a Survey Forest Diagram to assist novice researchers in developing divergent thinking and expanding their perspective when exploring research topics using Generative AI, addressing the challenge of information overload.
Contribution
It proposes a novel visualization tool, the Survey Forest Diagram, that guides divergent thinking and citation exploration for research surveys, especially aiding novices.
Findings
Enhanced survey perspective for novice researchers
Effective citation clue visualization method
Supports divergent thinking in research exploration
Abstract
With the exponential growth in the number of papers and the trend of AI research, the use of Generative AI for information retrieval and question-answering has become popular for conducting research surveys. However, novice researchers unfamiliar with a particular field may not significantly improve their efficiency in interacting with Generative AI because they have not developed divergent thinking in that field. This study aims to develop an in-depth Survey Forest Diagram that guides novice researchers in divergent thinking about the research topic by indicating the citation clues among multiple papers, to help expand the survey perspective for novice researchers.
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