A Web-Based Platform for Annotating Sentiment-Related Phenomena in Human-Agent Conversations
This paper introduces a web-based platform dedicated to the annotation of sentiment-related phenomena in human-agent conversations. The platform focuses on verbal content and deliberately sets aside non-verbal features. It is designed for managing two dialogue features: adjacency pair and conversation progression. Two annotation tasks are considered: (i) the detection of sentiment expressions, (ii) the ranking of user’s preferences. These two tasks focus on a set of specific targets. With this demonstration, we aim to introduce this platform to a large scientific audience and to get feedback for future improvements. Our long-term goal is to make the platform available as open-source tool.
KeywordsVerbal content annotation Virtual agent Sentiment analysis
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