# Towards User-Centric Guidelines for Chatbot Conversational Design

arXiv: https://arxiv.org/abs/2301.06474 · HTML: https://mlsanity.com/paper/2301.06474/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2023.

## Built on by (most cited first, 6 of 6)

- [On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models](https://mlsanity.com/paper/2403.04204/) (2024)
- [Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives](https://mlsanity.com/paper/2507.15783/) (2025)
- [Script-Strategy Aligned Generation: Aligning LLMs with Expert-Crafted Dialogue Scripts and Therapeutic Strategies for Psychotherapy](https://mlsanity.com/paper/2411.06723/) (2024)
- [Towards the design of user-centric strategy recommendation systems for collaborative Human-AI tasks](https://mlsanity.com/paper/2301.08144/) (2023)
- [Human Tool: An MCP-Style Framework for Human-Agent Collaboration](https://mlsanity.com/paper/2602.12953/) (2026)
- [Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study](https://mlsanity.com/paper/2609.14236/) (2026)

## Abstract (arXiv)

The conversational nature of chatbots poses challenges to designers since their development is different from other software and requires investigating new practices in the context of human-AI interaction and their impact on user experience. Therefore, this work aims to unveil chatbot conversational practices alongside their impacts on users to build a web guide to support designers while conceiving conversations for chatbots. We have carried out a Systematic Literature Review (SLR) to identify linguist, visual, and interactive elements used in chatbot conversational design. The SLR resulted in 40 selected studies that were reviewed and coded into a set of conversational guidelines that were evaluated through a survey. Respondents strongly agreed that applying the proposed guidelines in chatbot development would induce greater user satisfaction and user engagement and the guide is usable, flexible, clear, and understandable, making it a great ally in building chatbots with an improved user experience.