Alan Abrahams

Associate Professor, Business Information Technology
Alan Abrahams
2068 Pamplin

Alan Abrahams is an Associate Professor in the Department of Business Information Technology, with research interests in quality analytics from text, specifically discovery of product defects from online reviews. Alan has publications in Production and Operations Management, Decision Support Systems, and Expert Systems with Applications in these areas. He is the faculty lead for PamTAT (Pamplin Text Analytics Toolbox), an easy-to-use Excel workbench for acquisition, transformation, and analysis buy essays online of text from social media, the web, and text files. With Rich Gruss, he has created PamTag, a large-scale collaborative tagging platform for online reviews, and has led the development of PamFlag, a collaborative-tagging extension for the Google Chrome web-browser.   These practical toolboxes are center-piece resources for the Center for Business Intelligence and Analytics, and facilitate rapid text analytics for members of the Virginia Tech community, and for collaborators in industry and government.

Dr. Abrahams eceived a PhD with a major in Computer Science from the University of Cambridge, and a Bachelor of Business Science degree with a major in Information Systems from the University of Cape Town.

Research

The Quality Analytics Consortium (QAC) is an industrial affiliate program that connects organizations with leading quality analytics research faculty and students within the Pamplin College of Business. Pooling the resources of multiple quality-focused organizations, QAC can provide consortium members with affordable access to valuable reports from Virginia Tech’s proprietary internal quality analytics software tools – PamTAT and PamTag. Under sponsored-research contracts, members may sponsor the acquisition of proprietary commercial datasets consisting of millions of industry-specific online discussions, or may supply their own internal textual sources, such as reviews and emails, for quality scoring and analysis. Consortium members benefit from Virginia Tech’s nationally recognized expertise in defect discovery and innovation opportunity identification.

QAC is supported by the Pamplin College’s Center for Business Intelligence and Analytics. QAC’s research priorities are guided by an Advisory Tier of Consortium Members. A variety of membership tier levels with varying benefits are available to cater to different budgets and needs.

For more information, contact Dr. Alan Abrahams, Associate Professor, Business Information Technology, abra@vt.edu or 540-231-5887.

Smoke Words: Media Mining to Find Vehicle Defects  - Can social media postings by consumers be a source of useful information about vehicle safety and performance defects for automobile manufacturers?

Researchers Mine Online Consumer Reviews to Identify Unsafe Toys - A Virginia Tech research project led by Alan Abrahams has found that text mining can help researchers make more effective use of the data in millions of consumer reviews posted online to identify toys with potential hazards.

America Business Law Journal

Healthy Predictions? Questions for Data Analytics in Healthcare

Janine S. Hiller

American Business Law Journal

Volume 53, Issue 2, pages 251-314, Summer 2016

Intelligence and Security Informatics

Predicting Vehicle Recalls with User-Generated Contents: A Text Mining Approach

X. Zhang, S. Niu, D. Zhang, G.A. Wang, W. Fan (2015).

Intelligence and Security Informatics,

Lecture Notes in Computer Science Volume 9074, pp 41-50

DOI: 10.1007/978-3-319-18455-5_3

Production and Operations Management

An Integrated Text Analytic Framework for Product Defect Discovery

Production & Operations Management  Published online 3 Nov 2014.

DOI: 10.1111/poms.12303

5-year ISI impact factor (2013):  2.378.

Production and Operations Management is among Business Week’s 20 Premier Journals and among Financial Times Research’s 45 Premier Journals.

Decision Support Systems

What’s buzzing in the blizzard of buzz? Automotive component isolation in social media postings.

Abrahams AS, Jiao J, Fan W, Wang GA, Zhang Z (2013).

Decision Support Systems, 55 (4) 871-882.

DOI: 10.1016/j.dss.2012.12.023

5-year ISI impact factor (2013): 2.651.

Decision Support Systems

Vehicle Defect Discovery from Social Media.

Abrahams AS, Jiao J, Wang GA, and Fan W (2012).

Decision Support Systems, 54 (1) 87-97.

DOI: 10.1016/j.dss.2012.04.005

5-year ISI impact factor (2013): 2.651.

Decision Support Systems

A Decision Support System for Patient Scheduling in Travel Vaccine Administration

Alan S. Abrahams, Cliff T. Ragsdale

Decision Support Systems

Volume 54, Issue 1, pages 215-225

Popular Press

The New York times logo

Can data stop car wrecks?

March 27, 2015

http://www.nytimes.com/2015/03/29/opinion/sunday/can-data-stop-car-wrecks.html?_r=0

Automotive News logo

Social Media Emerges as Tool to Find Defects

January 22, 2013

http://www.autonews.com/article/20130122/OEM11/130129984/social-media-emerge-as-tool-to-find-defects

Law DS; Abrahams AS, and Gruss R. Automated defect discovery for dishwasher appliances from online consumer reviews.  Expert Systems with Applications (Accepted 29th August 2016). Forthcoming.  5-year ISI Impact Factor (2015): 2.879.  In 2016, ESWA is ranked #1 among Artificial Intelligence journals by Google Scholar.

Winkler M, Abrahams AS, Gruss R, Ehsani J (2016).
Toy Safety Surveillance from Online Reviews.
Decision Support Systems.  Forthcoming.
Accepted 20 May 2016

5-year ISI impact factor (2015):  3.271.
Production and Operations Management is among Business Week’s 20 Premier Journals and among Financial Times Research’s 45 Premier Journals.

Abrahams AS, Fan W, Wang GA, Zhang Z, Jiao J (2015).
An Integrated Text Analytic Framework for Product Defect Discovery.
Production & Operations Management.  Published online 3 Nov 2014.
DOI: 10.1111/poms.12303

5-year ISI impact factor (2013):  2.378.
Production and Operations Management is among Business Week’s 20 Premier Journals and among Financial Times Research’s 45 Premier Journals.

Zhang, S. Niu, D. Zhang, G.A. Wang, W. Fan (2015).
Predicting Vehicle Recalls with User-Generated Contents: A Text Mining Approach

Intelligence and Security Informatics,
Lecture Notes in Computer Science Volume 9074, pp 41-50
DOI: 10.1007/978-3-319-18455-5_3

Abrahams AS, Jiao J, Fan W, Wang GA, Zhang Z (2013).
What’s buzzing in the blizzard of buzz? Automotive component isolation in social media postings. Decision Support Systems, 55 (4) 871-882.
DOI: 10.1016/j.dss.2012.12.023
5-year ISI impact factor (2013): 2.651.

Abrahams AS, Jiao J, Wang GA, and Fan W (2012).
Vehicle Defect Discovery from Social Media. Decision Support Systems, 54 (1) 87-97. DOI: 10.1016/j.dss.2012.04.005
5-year ISI impact factor (2013): 2.651.