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A Computational Literature Analysis of Conversational AI Research with a Focus on the Coaching Domain

17 pagesPublished: June 20, 2022

Abstract

We conduct a computational analysis of the literature on Conversational AI. We identify the trend based on all publications until the year 2020. We then concentrate on the publications for the last five years between 2016 and 2020 to find out the top ten venues and top three journals where research on Conversational AI has been published. Further, using the Latent Dirichlet Allocation (LDA) topic modeling technique, we discover nine important topics discussed in Conversational AI literature and specifically two topics related to the area of coaching. Finally, we detect the key authors who have contributed significantly to Conversational AI research and area(s) related to coaching. We determine the key authors' areas of expertise and how the knowledge is distributed across different regions. Our findings show an increasing trend and thus, an interest in Conversational AI research, predominantly from the authors in Europe.

Keyphrases: Coaching, Computational Literature Analysis, Conversational AI, Latent Dirichlet Allocation

In: Knut Hinkelmann and Aurona Gerber (editors). Proceedings of the Society 5.0 Conference 2022 - Integrating Digital World and Real World to Resolve Challenges in Business and Society, vol 84, pages 100--116

Links:
BibTeX entry
@inproceedings{Society5.0-2022:Computational_Literature_Analysis_of,
  author    = {Charuta Pande and Hans-Georg Fill and Knut Hinkelmann},
  title     = {A Computational Literature Analysis of Conversational AI Research with a Focus on the Coaching Domain},
  booktitle = {Proceedings of the Society 5.0 Conference 2022 - Integrating Digital World and Real World to Resolve Challenges in Business and Society},
  editor    = {Knut Hinkelmann and Aurona Gerber},
  series    = {EPiC Series in Computing},
  volume    = {84},
  pages     = {100--116},
  year      = {2022},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {https://easychair.org/publications/paper/K2DT},
  doi       = {10.29007/lh9r}}
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