Library and Information Science faculty members Chirag Shah and Mor Naaman, together with Stevens Institute faculty member Winter Mason, have been awarded $219,126 by the National Science Foundation (NSF) for the project "Building Communities for Transforming Social Media Research with SOCRATES:Â SOcial and CRowdsourced AcTivities Extraction System".
The two-year project, for which Shah will serve as Principal Investigator (PI) and Naaman and Mason as co-PIs, will result in a novel system called SOCRATES that will transform social media research for scholars working in diverse fields by building a community of researchers and practitioners around various issues of data-intensive research. Social media services such as Twitter and Facebook, used by millions of people worldwide, expose vast amounts of data about peopleâ€™s beliefs, ideas, opinions, behaviors, and activities. At the same time, the sheer scale and volume of the data make them extremely difficult for scholars to study effectively. SOCRATES will address this issue by incorporating a set of socio-computational tools that will allow researchers from multiple fields to collect large-scale social media data; explore and visualize the resulting content items, and analyze the collected content. A community- and human-centered approach to developing the new system will ensure that SOCRATES matches researchersâ€™ work practices and mental models, is easy to use, and produces outcomes that significantly contribute to the researchersâ€™ goals, especially in solving multi-disciplinary problems.
Importantly, the SOCRATES system will employ a social-computational approach--crowdsourcing--to handle some of the challenges of social media research. Thus, the project will take advantage of the intelligence of both computers and people to study online social activities. SOCRATES proposes to use the labor of humans to assist in the collection of data (e.g., by refining and filtering information collected by an automatic crawler); to help explore the data and generate insights (e.g., by allowing the public to view and comment on visualizations of the collected data); and to analyze and annotate the data (e.g., by creating a controlled environment where coders can annotate content items with high reliability). As a result, SOCRATES will provide a first-of-its-kind, end-to-end environment where social media can be studied effectively, with high validity, and at immense scale.
"As analyzing social media data has become an increasingly popular method of investigation by researchers in a variety of fields, the need for creating and supporting infrastructure and communities around such activities has become highly important,â€ť said Shah. Â â€śThis project, SOCRATES, is meant to meet that need by creating a platform of tools, services, and methods, allowing social and computational scientists to collaborate around social media data, techniques, and analyses. This will result in not only better understanding of people's behaviors and opinions on topics of interest, but also in a community of scholars and practitioners around a common platform."
The funding for this project is part of the NSF's Building Community and Capacity for Data-Intensive Research in the Social, Behavioral, and Economic Sciences and in Education and Human Resources (BCC-SBE/EHR) program in which,Â as part of NSF's Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) activity which seeks to enable research communities to develop visions, teams, and capabilities dedicated to creating new, large-scale, next-generation data resources and relevant analytic techniques to advance fundamental research for the SBE and EHR sciences.Â Successful proposals outline â€śactivities that will haveÂ significant impacts across multiple fields by enabling new types of data-intensive researchâ€ť, whereinÂ â€śinvestigators think broadly and create a vision that extends intellectually across multiple disciplines and that includes--but is not limited to--the SBE or EHR sciences.â€ťÂ Visit the BCC-SBE/HER web site at NSF http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504747&org=NSF&sel_org=XCUT&from=fund for more details.