A fall 2011 briefing for personnel at Forrester in Cambridge MA.

1. The Future of Text AnalysisDr. Stuart ShulmanTexifter, LLC Wednesday, June 15, 2011

2. Briefing Agenda R&D in Annotation and Public Comments “The Future of Text Analysis” – The vision “What is DiscoverText?” – The software The Features – The basics Capturing social media importing other text Creating archives, buckets and datasets Coding a dataset or training a classifier

3. Dr. Stuart W. Shulman Founder & CEO, Texifter, LLCAssistant Professor, Department of Political ScienceUniversity of Massachusetts Amherst Director, Qualitative Data Analysis Program (QDAP)Associate Director, National Center for Digital Government Editor, Journal of Information Technology & Politics 413-545-5375 stu@polsci.umass.eduhttp://people.umass.edu/stu/

7. The Future of Projects Projects leverage users’ credentials to control access to documents, tools, and resources Major Project Components Credentials Documents Peers Advanced ‘Social’ Search Metadata Networks Filtering Tools for Tagging Shared Analysis Qualitative & Quantitative Findings

8. The Future of Documents Import & archive data from multiple sources into a single, searchable, unified repository

9. The Future of Search eDiscovery will search, merge, filter & classifyunlimited amounts of text and other data

10. Well Worth Reading

11. The Future of Tools Text processing tools will enable quicker processing and more accurate results

12. The Future of Peer Relations Utilize trusted peers to scale your knowledge resources, increase productivity & lower total project costs

13. Peers Groups Securely segment your peers into project groups by agency, firm, department, location, or affiliation, while controlling their access via credentials

14. Security & Credentials Data will be encrypted, secure and accessible by only peers who are granted specific permissions via their credentials

15. Coding, Tagging or Labeling Annotation enhances your analysis by applying human interpretation to machine results

16. Coding in Flexible Teams

17. Crowdsourcing Crowdsourcing will bring widely distributed wisdom to process of text analysis “This is really the biggest paradigm shift in innovation since the Industrial Revolution” - MIT professor Eric von Hippel, specialist in innovation management

18. Active Machine Learning By utilizing information and decisions previously captured, we can enhance future machine-based decisions Active Learning Loop

19. What is DiscoverText? DiscoverText is a: personal or organizational archive in the cloud search engine for eDiscovery social media comment aggregator de-duplication and near duplicate clustering engine FOIA redaction toolkit coding, reporting and validation team workbench repository of human annotation (text about text), and customizable machine-learning classifier (beta launched April 2011)