ABSTRACT

This study analyzed Twitch chat messages for verbal indicators of the presence of parasocial relationships. Unlike traditional parasocial research, this study employed natural language processing to score streamer-targeted and viewer-targeted messages for verbal immediacy. It divided chat data according to stream content and streamer type and found that streamer-targeted messages consistently scored higher in verbal immediacy than viewer-targeted messages. The verbal immediacy scores for this dataset were content-agnostic. The findings illustrated a new method for testing the perceived relational closeness of parasocial relationships, namely, utilizing user-generated content to identify verbal indicators of parasocial relationships. Researchers are now capable of exploring the variance of parasocial relationships as they are naturally presented through new media platforms, where media users and figures co-exist.

抽象的

这项研究分析了Twitch聊天消息中是否存在超社会关系的口头指示。与传统的超社会研究不同，这项研究采用自然语言处理来对口头针对性和观众针对性的信息进行口头即时性评分。它根据流内容和流媒体类型对聊天数据进行了划分，发现以流媒体为目标的消息在言语即时性方面的得分始终高于以观看者为目标的消息。此数据集的口头即时得分与内容无关。调查结果说明了一种新方法，用于测试所感知的超社会关系的亲密性，即利用用户生成的内容来识别超社会关系的口头指标。