Hamlet II: Textual quantitative analysis
Studies in social sciences often make use of quantitative text analysis to analyse trends in data, particularly primary data. Quantitative analyses of textual data help in validation statistics, co-occurrences of words/texts, textual trends, and frequency statistics. A number of tools have been developed to help in textual analyses of text based data. Hamlet II is one of the most efficient and user-friendly ones.
Basics of Hamlet II for quantitative text analysis
Hamlet II helps in quantitative analysis of text. It offers a multidimensional scaling approach. It also serves as computer assisted text analysis. It shows the differences of the basis of types of analyses, and ease of usage. This software allows a range of statistical models such as Jaccard coefficient, Sokal’s matching coefficient, and van Eck and Waltman’s proximity, PINDIS, INDSCAL, MDPREF, MRSCAL and MINISSA. Hamlet II also uses critical algorithms for statistical analysis of text. It is compatible with .doc, .docx, .txt, .csv, .pdf and other common file types.
The software has different file formats or extensions depending upon the type of analysis. Therefore, it is very important to... More
Hamlet II is an approach to quantitative text-based analytical software. This article reviews the difference between them and Hamlet II.... More
Word or text based analysis with Hamlet II
This section will explain numerous descriptive analyses that can be performed for quantitative text analysis. The simplest descriptive analysis is text frequency analysis Wordlist. The articles will explain the steps and methods to conduct Wordlist analysis, along with its interpretations. This section also covers articles on steps to form vocabulary list for the transcripts imported to the software. Graphical presentation of the word frequency has also been covered in this module. Next, it covers the steps to analyze keywords in context and joint frequencies in Hamlet II.
Quantitative analysis of textual data has been long used in the field of social sciences research. This includes data collected... More
This article presents the steps to perform frequency analyses which are, keyword in-context or KWIC and graphical analysis of wordlist... More
Hierarchical clustering uses methods to segregate the texts according to the similar vocabularies and then similar words or context are clustered together.
Non-hierarchical cluster analysis is the next step to a hierarchical cluster model. It allows the partitioning of the similar matrices... More
Cluster and correspondence analysis and multidimensional scaling with Hamlet II
Cluster and correspondence analysis, and Multidimensional scaling is usefull for presenting critical and graphical analysis. It presents the methods and steps to conduct the models such as PINDIS, INDSCAL, MDPREF, MINISSA and LDA.
This article talks about the application of Singular Value Decomposition (SVD) technique MDPREF using Hamlet II. It is performed on... More
This article explains how to perform metric multidimensional scaling method MRSCAL in Hamlet II. MRSCAL stands for metric scaling.