Collaborative Research: BCC-SBE: Building Communities for Transforming Social Media Research with SOCRATES: SOcial and CRowdsourced AcTivities Extraction System

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This project will result in a novel system called SOCRATES that will help 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 people'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 researchers' work practices and mental models, is easy to use, and produces outcomes that significantly contribute to the researchers' 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.