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SOCRATES, is a social-computational system and platform for the study of social media using crowdsourcing. The project will develop a framework and a technical system through which researchers can collect content from one or more social media sources, explore the collected content to help generate hypotheses, and analyze the content the content to produce insights, findings, and research results in true social-computational scale.

The SOCRATES Architecture


The SOCRATES Collect component will provide seamless support for collecting vast amounts of data from social media sites easily and effectively. This interactive component will let the researchers specify their needs quickly and intuitively (e.g., using keywords with source-selection), get them data from these disparate data sources, transform the data into standardized structured formats, and allow easy modification to initial setup and criteria for data collection. One of the important lessons learned from previous experiences, as well as preliminary investigations, is that such a component should be easily integrated into existing systems and practices. The project will therefore address the challenge of collecting large amounts of social media data with minimal effort on the researchers’ end, in terms of learning new environments or assuring proper workflow with their existing systems.


The SOCRATES Explore component will offer visualizations of the data that enable targeted exploration, allowing researchers to gain understanding and insight into the data independently. The project will develop an interactive application that allows researchers to examine the collected material along multiple dimensions: being able to explore high-level aggregate trends, alongside individual content items (“overview first, details on demand” is a related idea in the visualization community). The researchers will be able to share the interactive visualization and data collected with others, to help “crowdsource” the exploration and hypothesis generation process. Users will be able to explore, comment, and provide insights in a way that enriches the data, and to provide new hypotheses about it to the researchers.


To analyze social media data at scale, SOCRATES will support efficient, accurate, and valid annotation of the collected content using a specialized crowdsourcing environment. The purpose of such annotation is multifaceted, including but not limited to categorization leading to evidentiary inferences or hypothesis testing by social scientists and algorithm development by information scientists.

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Dr. Chirag Shah

PI Chirag Shah at Rutgers will direct the overall research and project management. Shah, with the help of the PhD student on this project, will coordinate all communications between the Rutgers and Stevens research teams and will be responsible for arranging regular meeting times.

Dr. Chirag Shah is an assistant professor of Information Science and an affiliate member of Computer Science at Rutgers University.

PhD in Information Science from UNC Chapel Hill

Dr. Mor Naaman

PI Naaman will supervise the development of the Explore component of SOCRATES.

Dr. Mor Naaman is an associate professor at Cornell Tech, where he is one of the first faculty at the Jacobs Technion Cornell Innovation Institute.

Ph.D. in Computer Science from Stanford University

Dr. Winter Mason

PI Mason will focus on Analyze aspects by integrating the processes with existing crowdsourcing technologies.

Dr. Winter Mason is an assistant professor at Stevens Institute of Technology.

Ph.D. in Social Psychology from Indiana University Bloomington

Ziad Matni

Ziad Matni is a doctoral student at SC&I-Rutgers, doing research in Information Science. His over-arching goals include to better understand why and how we use ICTs (specifically, social media). He is interested in using social media tools in novel ways to help us understand new and interesting things about ourselves, our social networks, our communities, and our neighborhoods. Ziad has a masters of science in electrical engineering from the University of Southern California and worked in several engineering and management positions in the electronics communication industry for about 13 years before turning to academia. Personal website.

Dongho Choi

Dongho Choi is a doctoral student in Library and Information Science at Rutgers University. He is interested in people's information behavior on social media, specifically in the context of business: product/service consumption, word of mouth, corporate strategy. He has educational background in Computer Science, Economics, and Business and worked at Samsung Electronics for 3 and half years as an engineer.

Kevin Albertson

Kevin Albertson is currently an undergraduate student at Rutgers University majoring in Computer Science and Mathematics. He plans on pursuing research after his undergraduate studies. His main experience is in web and game development but he continues exploring a variety of interests.