Intergroup comparision of emotions.

Communication within online platforms supported by chatbots requires algorithms, language processing methods, and an effective visual representation. These are crucial elements for increasing user engagement and making communication more akin to natural conversation. Chatbots compete with other graphic elements within websites or applications, and thus attracting a user’s attention is a challenge even before the actual conversation begins. A chatbot may remain unnoticed even with sophisticated techniques at play. Drawing attention to the chatbot area localized within the periphery area can be carried out with the use of various visual characteristics. The presented study analyzed the impact of changes in a chatbot’s emotional expressions on user reaction. The aim of this study was to observe, based on user reaction times, whether changes in a chatbot’s emotional expressions make it more noticeable. The results showed that users are more sensitive to positive emotions within chatbots, as positive facial expressions were noticed more quickly than negative ones.

由聊天机器人支持的在线平台通信，需依托算法、语言处理方法与有效的视觉呈现方案。此三者均为提升用户参与度、使沟通更贴近自然对话的核心要素。聊天机器人需与网站或应用内的其他图形元素争夺视觉注意力，因此即便在实际对话启动前，吸引用户关注便已是一项挑战。即便采用了先进的技术手段，聊天机器人仍有可能被用户忽略。可通过多种视觉特征，将用户注意力引导至界面边缘区域内的聊天机器人界面。本研究分析了聊天机器人情绪表达变化对用户反应的影响。本研究旨在基于用户反应时，观察聊天机器人的情绪表达变化是否能提升其被关注度。研究结果表明，用户对聊天机器人的正向情绪更为敏感，相较于负面面部表情，正向面部表情能被更快识别。