The overall goal of this project is to explore and establish a better understanding of privacy in this highly-networked world. This page features the tools and workflow needed to accomplish such a task. We argue that while much has been written and discussed about privacy in various domains (e.g., law, psychology, economic behavior, security, etc.), it remains unclear what exactly is the privacy problem?
Our aim is to reframe our own understanding of privacy by moving away from these traditional disjointed compartments of knowledge. Moreover, given the complexity, we advocate this research question as an exemplar for the value of combining efforts between human and machine. This project features tools, workflow(s) and best practices we've developed and implemented to accomplish such a task.
For example, while we leverage existing data mining & sentiment analysis techniques on social network data for empirical results, we also place an emphasis on capturing the qualitative information through semantic annotations (like resources and certain keywords, dates, topics were chosen etc.). The tools and workflow attempt to bridge the gaps in methodological approaches and between research domains.
More importantly as researchers, it is imperative that we move beyond flat, single-dimensional readings of data. Instead, to define and address issues of social complexity like privacy, a more comprehensive, 360 degree, deep understanding is needed. This is and will be a work in progress. Any comments and or feedback are welcomed. Please email Kristine Gloria at glorim@rpi.edu for more information.
