Beyond Dyadic Interactions

Abstract

Chatbots have grown as a space for research and development in recent years due both to the realization of their commercial potential and to advancements in language processing that have facilitated more natural conversations. However, nearly all chatbots to date have been designed for dyadic, one-on-one communication with users. In this paper we present a comprehensive review of research on chatbots supplemented by a review of commercial and independent chatbots. We argue that chatbots' social roles and conversational capabilities beyond dyadic interactions have been underexplored, and that expansion into this design space could support richer social interactions in online communities and help address the longstanding challenges of maintaining, moderating, and growing these communities. In order to identify opportunities beyond dyadic interactions, we used research-through-design methods to generate more than 400 concepts for new social chatbots, and we present seven categories that emerged from analysis of these ideas.

Conversation dynamics in a multiplayer video game with knowledge asymmetry

“…Previous research has explored the development of artificial agents that can comprehend (e.g., ( Blukis et al, 2018 ; Misra et al, 2018 )) and produce language input (e.g., ( Abramson et al, 2020 , 2021 )) in instruction-following tasks using supervised learning techniques. However, this research, as well as most commercially available conversational platforms used today (e.g., Amazon’s Alexa, Google’s Dialogflow) rely on dyadic, question-response interactions ( Seering et al, 2019 ). To enable conversational agents to function in team-based tasks such as the one employed in this study, such agents need to be able to monitor the conversations of all team members and to develop expertise in anticipating what and when information will be requested by the team members ( Simpson and Crone, 2021 ).…”

Reminders, reflections, and relationships: insights from the design of a chatbot for college advising

“…When deployed in China, XiaoIce embraced a persona of an 18-yearold girl who was always loving and empathetic (Zhou et al, 2020). Another example of designing purposeful personas is in integrating social roles into chatbots to cater to different platform purposes, such as an authority figure bot that punishes wrongful behaviors, a novice that learns alongside users or a storyteller who advances narratives with user input (Seering et al, 2019).…”

Moderation Visibility: Mapping the Strategies of Volunteer Moderators in Live Streaming Micro Communities

“…Recent research about moderation in live streaming focused on the motivation of being a moderator [58], how moderators engage with their communities [51], and categorizing moderation tools [4]. However, there has been relatively less discussion about the onthe-ground moderation practices of volunteer moderators-namely what kinds of strategies they use, and how these strategies work together during the moderation process, a gap which the present work aims to fll.…”

“…The setting and application of AutoMod happened behind the scene, and the moderation process was invisible to the public. Applying moderation tools to block words is a common strategy that has been broadly discussed in online communities (e.g., [29,51,52]). 4.1.4 Seting a good example.…”

“…Recent work of volunteer moderators and moderation mainly focuses on user-governed platforms such as Wikipedia [11,33], and Reddit [9,16,29]. Twitch, as a user-moderated, live-streaming community, is similar in some governance aspects to other online communities such as Reddit, which is a self-reliant community [29], and Facebook Group, which provides multiparty interactions [51]. However, the interactivity of live streaming makes it diferent from other social platforms in mainly three aspects: 1) the large volume of messages generated and posted in a short time, 2) the fow speed of these messages in the chat, and 3) the limited time for the moderator to remedy harmful situations.…”