A method for automated language analysis based on word-selection, comprising the steps:
- a) preparing a computer system (1.30) by
- aa) storing a plurality of reference language files (1.10) in a memory unit (1.20) of the computer system (1.30) in order to form a reference sample (1.40), wherein each reference language file (1.10) comprises a minimum number of 100 words, and each reference language file (1.10) originates from a different person having known characteristics, the characteristics including personality traits,
- ab) storing a dictionary file (2.20) containing a multiplicity of different categories (2.10) in a memory unit (1.20) of the computer system (1.30), wherein all the words in the dictionary file (2.20) are classified in at least one of the categories (2.10),
- ac) making an individual comparison of each reference language file (1.10) in the reference sample (1.40) with the dictionary file (2.20) by calculating the percentage frequency (3.40) of occurrence of the words in each reference language file (1.10) that are contained in each category (2.10) of the dictionary file (2.20), and
- ad) storing a set of rules (5.40) in a memory unit (1.20) of the computer system (1.30), wherein the set of rules uses statistical and/or algorithmic methods to calculate associations at least between the percentage frequencies (3.40) calculated in step ac) in one or more categories (2.10) and at least one known characteristic (4.20) of the people from whom the reference language files (1.10) originate,
- b) following preparation of the computer system in accordance with steps aa)-ad), recording and storing a language file (6.10), in addition to the reference language files (1.10) of the reference sample (1.40), in a memory unit (1.20) of the computer system (1.30), wherein each language file (6.10) and each reference language file is one of a text file or an audio file that is converted into a text file by a transcription,
- c) analyzing the language file (6.10) additionally recorded and stored in step b), by
- ca) making an individual comparison of the language file (6.10) with the dictionary file (2.20) by calculating the percentage frequency (7.30) of the words in the language file (6.10) that are contained in each category (2.10) of the dictionary file (2.20), and
- cb) using the set of rules (5.40) to process the percentage frequencies (7.30) calculated in step ca), wherein the set of rules uses statistical and/or algorithmic methods to examine the percentage frequencies (7.30) calculated in step ca) for similarities with the percentage frequencies (3.40) calculated in step ac), and classifies the language file (6.10) according to the established similarities, and associates said file with at least one known characteristic belonging to the people from whom the reference language files (1.10) originate,
- d) creating an output file (8.20), which contains characteristics (4.20) associated with the language file (6.10) in step cb), and
- e) outputting the output file (8.20) by displaying the output file on a screen, outputting the output file using a speaker, transmitting the output file via a network, or printing the output file using a printer,
- f)
- fa) expanding the reference sample (1.40) in step aa) by adding as reference language files (1.10), each language file (6.10) recorded in step b),
- fb) providing a feedback through an input, which allows an evaluation of the correctness of the analysis of step c), and
- fc) updating and re-saving the set of rules (5.40) taking into account the enlarged database from step ad).