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dvancing important and practical research in the social sciences using advanced computational approaches is the focus of The Center for Computational and Data Sciences (CCDS). The Center builds on the iSchool’s historic strengths in human language technologies (such as natural language processing and machine learning) and a new emphasis on data science research. Researchers are doing work that advances the science of data collection, retrieval, curation, analysis and archiving. They are applying those techniques to provide needed expertise and systems to solve pressing social problems or needs by collecting large-scale behavioral, interactional and other data, then using data science processes and human language technologies to create solutions.
PROJECTS INCLUDE: TRACE The Trackable Reasoning and Analysis for Collaboration and Evaluation (TRACE) Project aims to improve reasoning and intelligence analysis by developing a web-based application to leverage the use of structured techniques, crowdsourcing and smart nudging to enhance analysts’ problem-solving abilities and foster creative thinking. The project is supported by a contract from the CREATE (Crowdsourcing Evidence, Reasoning, Argumentation, Thinking and Evaluation) Program of the Intelligence Advanced Research Projects Activity (IARPA), an arm of the Office for the Director of National Intelligence, which heads the nation’s intelligence services. Its first-phase funding is worth $5,215, 441. Led by Professor Jennifer Stromer-Galley, the initiative utilizes the expertise of a multi-disciplinary team of researchers from Syracuse University, the University of Arizona, Colorado State University, and SRC, Inc., a Syracuse-based company. (See article on page 14.) traceproject.syr.edu
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THE iSCHOOL @ SYRACUSE UNIVERSITY
Illuminating 2016 This computational journalism project was begun as a way to empower journalists covering the 2016 presidential campaign by providing a highly defined look at how candidates are expressing their views, platforms and election events via social media. The deep data-dive analysis of Twitter and Facebook posts by candidates has increased transparency and accountability of the campaigns, and has provided a way to tag the types, topics and strategies of candidate messages, as well as the public’s conversation. The project’s goal is to provide a useable yet comprehensive summary of the content of candidates’ social media posts, well beyond simply counting likes or retweets, especially due to the volume of information available. Illuminating 2016 was designed to enable political journalists an insightful yet accessible summation of the important political conversation online. (See article on page 12.) illuminating.ischool.syr.edu
Citation Opinion Retrieval and Analysis (CORA) The CORA Project aims to build an automated tool to plug into a full-text bibliographic database, extract citation statements toward a cited article, separate substantial citations from perfunctory ones and categorize substantial citation opinions by their purposes, subject aspects, tones, and holders and targets of the opinions. The tool’s goal is to save librarians and researchers significant amounts of time finding the most useful comments from a large number of citations. It also is designed to provide a new, qualitative approach for assessing research impact and can help monitor the quality of scientific publications by facilitating easier identification of citation bias and inaccurate citations from the re-organized citations. CORA will also contribute a new approach for assessing research impact and help monitor the quality of scientific publications. ccds.ischool.syr.edu/projects/cora/
