English

Defining and Quantifying Conversation Quality in Spontaneous Interactions

Multiagent Systems 2020-09-29 v1 Human-Computer Interaction

Abstract

Social interactions in general are multifaceted and there exists a wide set of factors and events that influence them. In this paper, we quantify social interactions with a holistic viewpoint on individual experiences, particularly focusing on non-task-directed spontaneous interactions. To achieve this, we design a novel perceived measure, the perceived Conversation Quality, which intends to quantify spontaneous interactions by accounting for several socio-dimensional aspects of individual experiences. To further quantitatively study spontaneous interactions, we devise a questionnaire which measures the perceived Conversation Quality, at both the individual- and at the group- level. Using the questionnaire, we collected perceived annotations for conversation quality in a publicly available dataset using naive annotators. The results of the analysis performed on the distribution and the inter-annotator agreeability shows that naive annotators tend to agree less in cases of low conversation quality samples, especially while annotating for group-level conversation quality.

Keywords

Cite

@article{arxiv.2009.12842,
  title  = {Defining and Quantifying Conversation Quality in Spontaneous Interactions},
  author = {Navin Raj Prabhu and Chirag Raman and Hayley Hung},
  journal= {arXiv preprint arXiv:2009.12842},
  year   = {2020}
}

Comments

10 pages, 8 figures, Companion Publication of the 2020 International Conference on Multimodal Interaction (ICMI '20 Companion), October 25--29, 2020, Virtual event, Netherlands

R2 v1 2026-06-23T18:49:31.350Z