Dynamic Visualization of Quality in Online Conversations

Brian Thoms, Evren Eryilmaz, N. Dubin, Rafael Hernandez, Sara Colon-Cerezo
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引用次数: 2

Abstract

This paper reports on software designed to visualize levels of quality within online conversational media. Prior to construction, data mining was performed on 2,157 online conversations and examined for attributes of quality. This initial dataset was analyzed for lexical complexity and prompt-specific vocabulary usage and helped guide the redesign of an existing asynchronous online discussion board (AOD). The new design incorporates a real-time quality analyzer and provides users with a visual breakdown of their post in relation to the overall group discussion thread. Results found that the proposed system produced higher levels of overall quality in discussion posts and increased interactions with higher quality discussion posts. Survey results and a social network analysis (SNA) indicate that the proposed system produced higher levels of system satisfaction and group cohesion when compared against control software.
在线对话质量的动态可视化
这篇论文报告了一种软件的设计,用于可视化在线对话媒体的质量水平。在构建之前,对2157个在线对话进行了数据挖掘,并检查了质量属性。我们分析了这个初始数据集的词汇复杂性和特定于提示符的词汇使用情况,并帮助指导对现有异步在线讨论板(AOD)的重新设计。新设计集成了实时质量分析器,并为用户提供了与整个小组讨论线程相关的帖子的可视化分解。结果发现,所提议的系统在讨论帖子中产生了更高水平的整体质量,并增加了与高质量讨论帖子的互动。调查结果和社会网络分析(SNA)表明,与控制软件相比,所提出的系统产生了更高水平的系统满意度和群体凝聚力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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