13:00:00 - 14:00:00,
Tuesday 9 September, 2014
In the last few decades, we have seen many new developments in domains related to text analysis, such as natural language processing, computational linguistic, information retrieval and text mining. Many of those developments were designed to provide new tools to analyze large collections of text data, extract information, identify patterns and discover hidden relationships. While some may adopt an optimistic view and see in those new methods as more efficient alternatives to the more traditional approaches to text analysis, a more realistic and pragmatic approach combining several methods is warranted. The presentation will attempt to illustrate some strengths and weaknesses of qualitative analysis, quantitative content analysis and text mining techniques and see how one could profit from combining different approaches and integrates existing techniques to achieve more valid and reliable conclusions. We will present an attempt to achieve such an integration in a software platform combining computer assisted qualitative analysis (QDA Miner) with quantitative text analytics techniques (WordStat).
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- Name: Normand Péladeau
- Affiliation: Provalis Research
- Bio: Normand Péladeau is the president and CEO of Provalis Research, a software company based in Montreal. He has a doctorate degree in psychology and more than 30 years of experience as a social science researcher and as a consultant in research methodology for large corporations, governmental agencies, and international organization. He trained hundreds of people to text analysis techniques for a wide range of applications such as business intelligence, market research, urban planning, aviation safety, media analysis, survey research, international crime analysis.