CCDS: Center for Computational and Data Sciences

Advancingimportant 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 languagetechnologies (such as natural language processing and machine learning) and a new emphasis on data science research.

Researchers are doing work that advances the scienceof 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-scalebehavioral, interactional and other data, then using data science processes andhuman language technologies to create solutions.

PROJECTS INCLUDE:

TRACE TheTrackable 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 theCREATE (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 ProfessorJennifer 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

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/

Inclusive Privacy Project This project aims to provide people with disabilities, particularly those with visual impairments, better privacy tools when working with computers.

To better understand the privacy challenges people with visual impairments face, this project first studies their computer use plus known technology privacy concerns. Researchers then work with people with visual impairments to generate, test and improve a number of design ideas that might address those challenges and concerns. They also work to generalize the studies and designs to other populations, including older adults who might have different privacy expectations than younger people as well as people with cognitive impairments. inclusiveprivacy.org/

Diffusion on Niche Social Media Sites Research This project studies the shift in information diffusion from large social media sites to niche social media sites. While information diffusion studies have mainly focused on sites like YouTube and Twitter, much less work has been done on the more than 400 smaller social media sites that tend to serve niche interests like art, music and academia.

The study looks at information diffusion through mixed methods, including interviews and computational work, with the purpose of understanding how diffusion is similar and different across a wide range of sites.

The CCDS Team Director: Professor Jennifer Stromer-Galley Also involved are: l Nancy McCracken, research associate professor l Jeff Hemsley, assistant professor l Yang Wang, assistant professor l Jeffrey Saltz, associate professor l Lu Xiao, associate professor l Bei Yu, associate professor l Daniel Acuna, assistant professor l Yatish Hegde, research staffmember l Kevin Crowston, associate dean for research l Patricia Rossini, postdoctoral researcher l Brian Semaan, assistant professor l Jennifer Grygiel, assistant professor of communications at the S.I. Newhouse School of Public Communications at Syracuse University l Rebekah Tromble, assistant professor in the Institute of Political Science at Leiden University, the Netherlands. Students include: Sikana Tanupabrungsun, Feifei Zhang, Brian Dobreski, Yingya Li, Mahboobeh Harandi, Jerry Robinson, Sam Jackson, Olga Boichak and Karen Hawkinson.

Deep Learning with TensorFlow Discussion CCDS hosted Roc Myers for a TensorFlow talk with interested graduate students and faculty. Myers serves as subject matter expert for CCDS’s TRACE project.

He has over 30 years of experience in intelligence systems’ operation and development and is the founder of Pertis. His company specializes in consulting and research of artificial intelligence and computer gaming technologies. Myers’ discussion explored uses and strategies for TensorFlow, an open source software library for numerical computation using data flow graphs.