In 2018, we introduced the possibility to create Python preprocessing scripts to WordStat 8. Version 9.0 extends this capability by offering the possibility to create preprocessing scripts in R as well. More importantly, it is now possible to create post-processing scripts in those two programming languages allowing one to perform custom analysis on the original or transformed text data or on quantified results obtained through content analysis on those documents. Such a feature offers endless possibilities to extend the features of WordStat such as implementing new machine learning algorithms, advanced statistical modeling techniques, or custom data transformation. Sample scripts have been included to compute text readability metrics, detect languages, apply other topic modeling techniques (LDA or STM) or create predictive models using machine learning (SVM, kNN, etc.).
A new file format with a new file extension (.pprj) was created, providing improved support for Unicode data. However, WordStat 9 retains backward compatibility with the prior versions of all our software and can open and analyze current project files (.ppj) created by QDA Miner, SimStat, or older versions of WordStat.
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The software gives HR managers a powerful tool to perform better and more meaningful analysis using existing processes or by developing new ones. HR managers are able to capture additional insights about their company, its strategies, and tactics, and use those insights to propose actionable plans to improve performance.
QDA Miner is the right tool to codify all types of interviews. Usually, this type of data needs to be codified manually and carefully. With more than seven text search tools, QDA Miner helps researchers to quickly retrieve all text segments related to a specific concept and carefully codify all sentences or paragraphs related to this concept. These features make the rapid categorization of large volumes of responses possible and effective. Once the coding is done, the advanced analysis features of QDA Miner such as clustering, multidimensional scaling, heatmaps, or correspondence analysis, allow HR managers to quickly retrieve comments about specific topics and explore relationships between concepts or topics. These are just a few examples of how you can use text analytics in Human Resources Management. There are many others. If you would like a demonstration of how our software can be part of your HR strategy, contact us at document.getElementById("eeb-900505-451819").innerHTML = eval(decodeURIComponent("%27%69%6e%66%6f%40%70%72%6f%76%61%6c%69%73%72%65%73%65%61%72%63%68%2e%63%6f%6d%27"))*protected email*. 2ff7e9595c
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