The automated analysis of digital human communication data often focuses on specific aspects like content or network structure in isolation, while classical communication research stresses the importance of a holistic analysis approach. This work aims to formalize digital communication analysis and investigate how classical results can be leveraged as part of visually interactive systems, which offers new analysis opportunities to allow for less biased, skewed, or incomplete results. For this, we construct a conceptual framework and design space based on the existing research landscape, technical considerations, and communication research that describes the properties, capabilities, and composition of such systems through 30 criteria in four analysis dimensions. We make the case how visual analytics principles are uniquely suited for a more holistic approach by tackling the automation complexity and leverage domain knowledge, paving the way to generate design guidelines for building such approaches. Our framework provides a common language and description of communication analysis systems to support existing research, highlights relevant design areas while promoting and supporting the mutual exchange between researchers. Additionally, our framework identifies existing gaps and highlights opportunities in research areas that are worth investigating further. With this contribution, we pave the path for the formalization of digital communication analysis through visual analytics.
翻译:人类数字通信数据自动化分析往往侧重于内容或网络结构孤立分析等具体方面,而古典通信研究则强调整体分析方法的重要性;这项工作旨在正式确定数字通信分析,并调查如何将古典成果作为视觉互动系统的一部分加以利用,从而提供新的分析机会,以便产生较少偏向、偏斜或不完整的结果;为此,我们在现有研究景观、技术考虑和通信研究的基础上,构建概念框架和设计空间,通过四个分析层面的30项标准,描述这些系统的特点、能力和构成;我们证明视觉分析原则如何特别适合采用更全面的方法,处理自动化的复杂性和利用域域知识,为制定建立这些方法的设计准则铺平道路;我们的框架提供了共同的语言和通信分析系统说明,以支持现有的研究,突出相关设计领域,同时促进和支持研究人员之间的相互交流;此外,我们的框架查明了在研究领域存在哪些差距和机会,值得进一步研究;我们通过这一贡献,为通过视觉分析使数字通信分析正规化铺平了道路。