  Chatbot has become an important solution to rapidly increasing customer care
demands on social media in recent years. However, current work on chatbot for
customer care ignores a key to impact user experience - tones. In this work, we
create a novel tone-aware chatbot that generates toned responses to user
requests on social media. We first conduct a formative research, in which the
effects of tones are studied. Significant and various influences of different
tones on user experience are uncovered in the study. With the knowledge of
effects of tones, we design a deep learning based chatbot that takes tone
information into account. We train our system on over 1.5 million real customer
care conversations collected from Twitter. The evaluation reveals that our
tone-aware chatbot generates as appropriate responses to user requests as human
agents. More importantly, our chatbot is perceived to be even more empathetic
than human agents.
