SearchBots: User Engagement with ChatBots during Collaborative Search

Abstract

Popular messaging platforms such as Slack have given rise to hundreds of chatbots that users can engage with individually or as a group. We present a Wizard of Oz study on the use of searchbots (i.e., chatbots that perform specific types of searches) during collaborative information-seeking tasks. Specifically, we study searchbots that intervene dynamically and compare between two intervention types: (1) the searchbot presents questions to users to gather the information it needs to produce results, and (2) the searchbot monitors the conversation among the collaborators, infers the necessary information, and then displays search results with no additional input from the users. We investigate three research questions: (RQ1) What is the effect of a searchbot (and its intervention type) on participants» collaborative experience' (RQ2) What is the effect of a searchbot»s intervention type on participants» perceptions about the searchbot and level of engagement with the searchbot' and (RQ3) What are participants» impressions of a dynamic searchbot? Our results suggest that dynamic searchbots can enhance users» collaborative experience and that the intervention type does not greatly affect users» perceptions and level of engagement. Participants» impressions of the searchbot suggest unique opportunities and challenges for future work.