Deepening our Empathy with the Many Voices of Society : A Social Psychological Approach to Information Search and Analytics

What does it take to extract an unbiased, informative, and human insight from the vast amount of information available through the World Wide Web, or any other source of textual content? We propose a new approach to information search and analytics that has two components. First, the design of a knowledge object that carries rich meta-cognitive data integrating the social, motivational, and emotional aspects that surround any issue of importance, which we call a Cogno-Material Object, and which forms the basic unit of analysis in our new approach. And second, a process for generating such meta-data, centered around a new and structured approach to web search which we call Associative Hyper-Search, to identify the specific motivations and emotions those providing the information associate with the issue. The combination of Cogno-Material Object and Associative Hyper-Search thus connects the informational content of the source data with the primary drivers of human decision-making, allowing us to gain deeper empathy with the many different cohorts of minds behind this content, and providing the basis for sharper insights and actionable conclusions. Here we present the first application of these ideas, with concrete examples drawn from the Web of 2021