BlahBlahBot:使用具有ml注入的个性化主题建议的聊天机器人促进陌生人之间的对话

Donghoon Shin, Sang-Taek Yoon, Soomin Kim, Joonhwan Lee
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引用次数: 12

摘要

在人们容易聚集的网络环境中,与陌生人聊天是一种普遍的行为。然而,由于缺乏关于陌生人的信息,人们常常发现很难发起和保持对话。因此,我们的目标是通过使用机器学习(ML)算法来促进陌生人之间的对话,并提出了BlahBlahBot,这是一个注入ML的聊天机器人,可以用个性化的话题来调节陌生人之间的对话。基于社交媒体帖子,BlahBlahBot通过建议用户之间可能共同感兴趣的话题来支持对话。三组用户研究(对照组、随机话题聊天机器人和BlahBlahBot;N=18)发现了BlahBlahBot在提高对话质量和与合作伙伴的亲密度方面的可行性,以及从用户访谈中导致这种增加的因素。总的来说,我们的初步结果表明,注入ml的会话代理可以有效地增强二元对话。
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BlahBlahBot: Facilitating Conversation between Strangers using a Chatbot with ML-infused Personalized Topic Suggestion
It is a prevalent behavior of having a chat with strangers in online settings where people can easily gather. Yet, people often find it difficult to initiate and maintain conversation due to the lack of information about strangers. Hence, we aimed to facilitate conversation between the strangers with the use of machine learning (ML) algorithms and present BlahBlahBot, an ML-infused chatbot that moderates conversation between strangers with personalized topics. Based on social media posts, BlahBlahBot supports the conversation by suggesting topics that are likely to be of mutual interest between users. A user study with three groups (control, random topic chatbot, and BlahBlahBot; N=18) found the feasibility of BlahBlahBot in increasing both conversation quality and closeness to the partner, along with the factors that led to such increases from the user interview. Overall, our preliminary results imply that an ML-infused conversational agent can be effective for augmenting a dyadic conversation.
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