SoCQA: Socio-computational qualitative analysis

This project explored the application of Natural Language Processing (NLP) and Machine Learning (ML) tools to the context domain of organizational behaviour, more specifically to a study of group maintenance in a novel setting. The project involved information scientists working collaboratively with domain scientists with the goal of developing an innovative NLP and ML-based research tool to support qualitative social science research, specifically content analysis.

Core-periphery communication and the success of free/libre open source software projects

Crowston, K., & Shamshurin, I.. (2017). Core-periphery communication and the success of free/libre open source software projects. Journal Of Internet Services And Applications, 8(10). https://doi.org/10.1186/s13174-017-0061-4

Design of an Active Learning System with Human Correction for Content Analysis

Yan, J. L. S., McCracken, N., & Crowston, K.. (2014). Design of an Active Learning System with Human Correction for Content Analysis. In Workshop on Interactive Language Learning, Visualization, and Interfaces, 52nd Annual Meeting of the Association for Computational Linguistics. Presented at the Workshop on Interactive Language Learning, Visualization, and Interfaces, 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, MD.

Semi-Automatic Content Analysis of Qualitative Data

Yan, J. L. S., McCracken, N., & Crowston, K.. (2014). Semi-Automatic Content Analysis of Qualitative Data. In iConference. Presented at the iConference, Berlin, Germany.

Optimizing Features in Active Machine Learning for Complex Qualitative Content Analysis

Yan, J. L. S., McCracken, N., Zhou, S., & Crowston, K.. (2014). Optimizing Features in Active Machine Learning for Complex Qualitative Content Analysis. In Workshop on Language Technologies and Computational Social Science, 52nd Annual Meeting of the Association for Computational Linguistics. Presented at the Workshop on Language Technologies and Computational Social Science, 52nd Annual Meeting of the Association for Computational Linguistics , Baltimore, MD.

Academic Year REU Intern Positions have been filled.

Submitted by Nancy McCracken on Sun, 2013-09-22 14:31

REU Research Intern Positions Available Fall 2013 and Spring 2014

Submitted by Nancy McCracken on Wed, 2013-08-21 08:37

Undergraduate Research Intern positions available for the academic year on-campus (fall 2013 and spring 2014). These positions are funded under the Research Experiences for Undergraduates (REU) program from the NSF and provide an $8,000 stipend paid over the academic year. Undergraduate students from information science, the social sciences and computer science who are interested in participating in an interdisciplinary research team are encouraged to apply by September 9, 2013.

Research Project Description

System Development Update

Submitted by Nancy McCracken on Fri, 2013-06-28 10:31

We have recently completed most of the functionality of the SoCQA tool. This includes ingesting the documents as annotated in Atlas-ti, learning a model from that data and reporting the model performance results, applying the model to additional data and allowing the user to verify whether the model predictions are correct or not.

System design and development update

Submitted by crowston on Wed, 2012-08-15 14:21

We're near the end of the 1st year of the grant and system development is progressing well, albeit a bit slower than we'd hoped. The high level system design is set and we've been implementing functionality in a series of sprints. By the end of the current sprint, we should have a basic system in place, allowing us to import email messages, import human annotations of some of the data from an Atlas-ti file, learn a model and apply the model to additional data. The final piece will be an interface to allow a human coder to correct the machine-applied annotations.

Tutorial introduction to content analysis

Here are the slides for the tutorial I gave on content analysis for the PI meeting for the NSF Socio-computational Systems (SoCS) program.