This is the homepage of HAMLET II - computer assisted text analysis

"Words, words, words." Hamlet (II,ii,194)

The main idea of HAMLET II^© is to search text files for words or categories in a given vocabulary list, and to count their joint frequencies within any specified context unit, within sentences, or as collocations within a given span of words.

This procedure is applicable when there are good grounds for searching for inter-connections between a number of key words, the spelling of which in the original text is already reasonably well known.

The benefit of measuring empirical properties of texts is nicely combined with HAMLET's features of graphical visualisation. Qualitative and quantitative analysis are integral parts of HAMLET's design. Unlike much other text analysis software, HAMLET provides maximum transparency of the processes involved, leaving the user in complete control.

Individual word frequencies (f_i) , joint frequencies (f_ij) for pairs of words (_i,_j), both expressed in terms of the chosen unit of context, and the corresponding standardised joint frequencies s_ij = (f_ij) / (f_i + f_j - f_ij) are organised in a similarities matrix, which can be submitted to a combination of cluster analysis and multi-dimensional scaling to discover significant word-associations. (Instead of the above (Jaccard) coefficient, it is possible to apply Sokal's 'matching coefficient', which takes account also of joint non-occurrences.) Word co-occurrences within specified context units can also be submitted to corrrespondence analysis, providing further information about usage within a text.

It then becomes possible to compare the results of applying multi-dimensional scaling to matrices of joint frequencies of equivalent vocabulary lists derived from a number of texts, using Procrustean Individual Differences Scaling (PINDIS), or to apply Individual Differences Scaling (INDSCAL) to the matrices themselves. Forrest Young's SUBJSTAT procedure transforming the resulting non-Euclidean 'subject spaces' into arc-distances permits more rigorous analysis of their results. Alternatively, the profiles of occurrences of items of a given search list in a number of different texts can be compared directly by correspondence analysis.

Further procedures help to determine the broad characteristics of word usage in a text:

WORDLIST generates lists of words and frequencies.
KWIC offers Key-Word-In-Context listings for any given word-string.
COMPARE lists words common to pairs of texts, and is useful in generating vocabulary lists, including synonyms, for use in comparing a number of texts. A series of texts may also be directly compared according to their vocabulary usage
PROFILE displays the distributions of word and sentence lengths in a text.

HAMLET II^© offers a unique Vocabulary Editor to speed up the development of vocabulary lists for use in researching co-occurrences and a new fast track procedure to apply them efficiently in comparing large numbers of texts in one operation, with PINDIS, INDSCAL or Correspondence Analysis.

The unique graphics of HAMLET II^© summarise the results of each of these analyses, for inclusion in other documents and reports. Numerical results can be saved, if necessary, in CSV format for further statistical analysis in STATA, Microsoft Excel or R.

Full documentation is available for HAMLET II new generation in the download section.
For running HAMLET II for Microsoft Windows using WINE on free Debian GNU/Linux consult our recent documentation Hamlet II on Debian GNU/LINUX!

Download HAMLET II

Download documentation

HAMLET tutorial (HTML)

Originators and sole distributors:
Alan Brier Associate Member, ESRC-National Centre for Research Methods, Southampton, UK
Bruno Hopp GESIS - Leibniz-Institut für Sozialwissenschaften, Cologne, Germany

Please address all enquiries and report any problems to