# A Measure for Dialog Complexity and its Application in Streamlining Service Operations

arXiv: https://arxiv.org/abs/1708.04134 · HTML: https://mlsanity.com/paper/1708.04134/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Aug 2017.

## Built on by (most cited first, 3 of 3)

- [Advances in Automatically Rating the Trustworthiness of Text Processing Services](https://mlsanity.com/paper/2302.09079/) (2023)
- [NatCS: Eliciting Natural Customer Support Dialogues](https://mlsanity.com/paper/2305.03007/) (2023)
- [Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube](https://mlsanity.com/paper/2402.01760/) (2024)

## Abstract (arXiv)

Dialog is a natural modality for interaction between customers and businesses in the service industry. As customers call up the service provider, their interactions may be routine or extraordinary. We believe that these interactions, when seen as dialogs, can be analyzed to obtain a better understanding of customer needs and how to efficiently address them. We introduce the idea of a dialog complexity measure to characterize multi-party interactions, propose a general data-driven method to calculate it, use it to discover insights in public and enterprise dialog datasets, and demonstrate its beneficial usage in facilitating better handling of customer requests and evaluating service agents.