DÉMOS WEB / WEBINAIRES

Provalis Research offrira désormais des démonstrations Web hebdomadaires gratuites pour les utilisateurs potentiels. N’hésitez pas à partager cette annonce avec vos amis et collègues.

Nous allons également créer des webinaires mensuels sur des sujets spécifiques ouverts à tous les utilisateurs. Nous recherchons des sujets ! Envoyez-nous vos idées par courriel à .

Chaque séance durera environ 45 minutes, fournira une introduction de base aux fonctions les plus importantes de QDA Miner et WordStat et vous permettra d’interagir directement avec un formateur expérimenté.

Pour ces démos web ou webinaires, vous avez besoin d’un ordinateur muni de haut-parleurs pour écouter et regarder la démo. Si vous avez des questions, vous pouvez les poser lors d’un chat pendant la présentation.

Si vous ne l’avez pas déjà fait, nous vous recommandons de télécharger la version d’essai de 30 jours de QDA Miner et WordStat avant de participer au webinaire, afin de vous familiariser avec le logiciel et de poser des questions plus ciblées pendant la présentation. Veuillez cliquer ici pour télécharger le logiciel d’essai gratuit.

En cliquant sur le lien suivant vous allez accéder à notre liste de webinaires et démonstrations :

Liste des webinaires et démos (en anglais)

Webinaires précédents sur des sujets spécifiques

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 datasets	Lucy McIntosh, Senior research assistant, The University of Hertfordshire
R34. Analyzing Russian Propaganda during 2020 Election Using Computer Learning Tools to Compare Media Content	Dr. 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 Strategy	Dr. Lcol. Nick Blas, University of Utah, International Relations and Comparative Politics
R31. What Can We Learn from 100 Novels? —A Text Analytic Dictionary Approach	Dr. Martin Gliserman , Professor, Rutgers University; Dr. Abby Jones, CEO, AJ RESEARCH
R30. Managing Project Risk Using the Voice of the Team (VoT) and Text Analytics	Dr. John Aaron, Project management and data science consultant, Milestone Planning & Research, Inc.
R29. Using Text Analytics For Optimizing Critical Decision Making	Dr. John Aaron, Project management and data science consultant, Milestone Planning & Research, Inc.
R28. Using Categorization Models for Confirmatory Approaches	Dr. Derrick L. Cogburn American University
R27. Use Stata & WordStat to analyze Twitter data to assess economic sentiment	Dr. Lydia Pik Yi Cheung, Auckland University of Technology David White, CEO, Survey Design
R26. Using the Unusual to Improve Content Analysis Research	Dr. Abby Jones AJ Research
R25. How to reveal the underlying intellectual structure of the domain with WordStat text mining software	Dr. Božidar Vlačić Catolica Porto Business School
R24. Use Text Analytics to Improve and Automate Analysis of Customer Comments	Jarle 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 projects	Mike Hine Sprott School of Business Carleton University
R21. What Are They Really Saying? Digging down into your Focus Group Data	Abby Jones AJ Research
R20. Balancing the insights of human interpretation with the power of qualitative software: analysing COVID-19 habits using WordStat and QDA Miner	Erik Wästlund Kalstad University Christina Silver University of Surrey
R19. Managing and analyzing focus groups and interviews with QDA Miner 6	Elif Kuş Saillard NAM Qualitative Research Center & Lab
R18. Competencies Needed for Success by U.S. Federal Employees	John 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 mix	Madalina 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 WordStat	Derrick L. Cogburn American University
R11. The danger of assumptions: Use WordStat to build codes in QDA Miner	Abby 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 Features	Normand Peladeau Provalis Research
R7. Overview of WordStat 7 Content Analysis and Text Mining features	Normand 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)

Démonstration en ligne sur vos propres données pour les entreprises et les institutions

Are you interested in introducing QDA Miner and WordStat to your company or institution? Contact us to set up an individual online demonstration for you and your team to learn more about the main features of our software and see how the software works on your own data. After the 45 minutes demonstration, there will be time to discuss any questions you might have. Schedule your individual demonstration by contacting us at: