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LEARNING
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LEARNING
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WEB DEMOS / WEBINARS / WORKSHOPS

Each session will last approximately 45 minutes, will provide a basic introduction to the most important QDA Miner and WordStat functions and will allow you to interact directly with an experienced trainer.

For these web demos or webinars, you need to have a computer with speakers in order to listen and watch the demo. If you have questions, you can chat in your questions during the presentation.

If you have not already done so, we recommend that you download the 30-day trial of QDA Miner and WordStat prior to attending the webinar, so that you can familiarize yourself with the software and ask more advanced questions during the presentation. Please click here to download the free trial software.

Lunch and Learns

Join us for a new series of online Lunch and Learn sessions!

The sessions are designed to help people learn more about the software and how it is used in practical situations. It will also introduce some of our trainers and consultants to a larger audience perhaps giving users a connection for further help or training.

In each session, we will feature a leading user of our software who will present on a topic in their area of expertise.

The sessions will last approximately one hour with a 30-45 minute presentation and a period for questions and answers. The presentations will be in English unless otherwise specified.

There is no cost to participate.

Title & descriptionDateHostLanguageRegistration
Understanding Causes of War, Qualitative Analysis of Diplomatic Archives.Wednesday, May 08 2024

12h-13h00 EDT
Matthieu Grandpierron
Associate professor of international relations and political science, Catholic University of Vendée.
EnglishSign up now

Previous webinars on specific topics

WEBINAR
PRESENTER
LINK
R40. Text Analytics for Business Forecasting and Financial Decision Making (Part 2)Dr. John Aaron and Paul Medioli,
Milestone Planning & Research, Inc
R39. Text Analytics for Business Forecasting and Financial Decision Making (Part 1)Dr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
Mikhail Golovnya, Senior Advisory Data Scientist, Minitab
R38. Uncovering Propaganda, Deception, and Bias in Media Reporting: Using Text Analytics as a Scientific Tool for Automatic Detection (Part 3)Dr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
R35. Uncovering Propaganda, Deception, and Bias in Media Reporting: Using Text Analytics as a Scientific Tool for Automatic Detection (Part 2)Dr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
R33. Uncovering Propaganda, Deception, and Bias in Media Reporting: Using Text Analytics as a Scientific Tool for Automatic Detection (Part 1)Dr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
R37. THE QUEST FOR VALIDITY:
Merging Deductive and Inductive Research Tools such as WordStat to Create More Valid Research Findings
Dr. Abby Jones
AJ Research
R36. No comment left behind: the use of computer-assisted coding in large datasetsLucy McIntosh,
Senior research assistant, The University of Hertfordshire
R34. Analyzing Russian Propaganda during 2020 Election Using Computer Learning Tools to Compare Media ContentDr. Sarah Oates, Professor and Sr. Scholar, University of Maryland
Dr. Abby Jones, AJ Research
R32. The Stories We Tell Ourselves: Using Text Analytics to Explore the Post 9/11 Strategic Narrative and its Influence on America’s Military StrategyDr. Lcol. Nick Blas, University of Utah, International Relations and Comparative Politics
R31. What Can We Learn from 100 Novels? —A Text Analytic Dictionary ApproachDr. Martin Gliserman , Professor, Rutgers University;
Dr. Abby Jones, CEO, AJ RESEARCH
R30. Managing Project Risk Using the Voice of the Team (VoT) and Text AnalyticsDr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
R29. Using Text Analytics For Optimizing Critical Decision MakingDr. John Aaron,
Project management and data science consultant, Milestone Planning & Research, Inc.
R28. Using Categorization Models for Confirmatory ApproachesDr. Derrick L. Cogburn
American University
R27. Use Stata & WordStat to analyze Twitter data to assess economic sentimentDr. Lydia Pik Yi Cheung, Auckland University of Technology
David White, CEO, Survey Design

R26. Using the Unusual to Improve Content Analysis ResearchDr. Abby Jones
AJ Research
R25. How to reveal the underlying intellectual structure of the domain with WordStat text mining softwareDr. Božidar Vlačić
Catolica Porto Business School
R24. Use Text Analytics to Improve and Automate Analysis of Customer CommentsJarle Hildrum
Senior Research Fellow
Telenor Group
R23. Exploring patients’ behavior through the collection and analysis of messages on healthcare forums
Thierry Baroghel
Focus Patient
R22. Dictionary-building process for use in text analytics projectsMike Hine
Sprott School of Business
Carleton University
R21. What Are They Really Saying? Digging down into your Focus Group DataAbby Jones
AJ Research
R20. Balancing the insights of human interpretation with the power of qualitative software: analysing COVID-19 habits using WordStat and QDA MinerErik Wästlund
Kalstad University
Christina Silver
University of Surrey
R19. Managing and analyzing focus groups and interviews with QDA Miner 6Elif Kuş Saillard
NAM Qualitative Research Center & Lab
R18. Competencies Needed for Success by U.S. Federal EmployeesJohn Ford
US Merit System Protection Board
R17. Presentation of QDA Miner 6 New Features
Normand Peladeau
Provalis research
R16. Big Data in Criminal Cases - Digital Evidence Analysis with QDA Miner and WordStat
Uwe Ewald
Internal Justice Analysis Forum
R15. Deductive Text Analytics: Using Categorization Models for Confirmatory Approaches and Hypothesis Testing
Derrick L. Cogburn
American University
R14. Mapping cognitive dissonance using QDA Miner and Wordstat within a methodological mixMadalina Manolach
University of Bucarest
R13. Analyse de données textuelles : approche qualitative ou machine learning? Un faux dilemme.Normand Péladeau
Provalis Research
R12. Entity extraction, topic modelling with WordStatDerrick L. Cogburn
American University
R11. The danger of assumptions: Use WordStat to build codes in QDA MinerAbby Jones
AJ Research
R10. How to perform sentiment analysis with WordStat 8 (part 2)Normand Peladeau
Provalis Research
R9. How to perform sentiment analysis with WordStat 8 (part 1)Normand Peladeau
Provalis Research
R8. QDA Miner 5 New FeaturesNormand Peladeau
Provalis Research
R7. Overview of WordStat 7 Content Analysis and Text Mining featuresNormand Peladeau
Provalis Research
R6. How to build categorization dictionaries with WordStat(soon)
R5. How to benefit from using the seamless integration of QDA Miner and WordStat(soon)
R4. How to analyze open-ended questions of surveys with QDA Miner and WordStat(soon)
R3. How to perform disambiguation of words with WordStat(soon)
R2. Automatic Document Classification feature of WordStat(soon)
R1. Presentation of the new features of WordStat 8(soon)

Online demonstration on your own data for companies and institutions