First Principles Selection of Social Media Visualizations
Abstract
The goal of this STTR is to develop methods and tools for the dynamic, automatic generation of social network analysis (SNA) visualizations, based on established principles from cognitive science and cognitive neuroscience. Accomplishing this will allow analysts to better understand networks as well as make unique discoveries that are primarily facilitated by the visualization (i.e., "a picture is worth a 1000 words"). While tables of data are exacting and detailed, it nevertheless can be difficult, if not impossible, to spot a particular trend or anomaly until one actually sees it effectively illustrated. Node-link diagrams have been traditionally used in the context of social network analysis, but these are not always helpful, nor appropriate. If a visualization does not convey notable patterns and trends in a way easily perceived by humans, its key insights are effectively hidden. The problem is thus not the data, but the vehicle to illustrate that data. Our work on this project will focus on generating visualizations that adhere to cognitive first principles, so that key insights are not only communicated, but so that humans can also easily perceive them.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 22, 2013
- Accession Number
- ADA582097
Entities
People
- Pedro Szekely