Figure 1
AVOBMAT graphical interface.
Figure 2
Interactive metadata visualization setting.
Figure 3
Network analysis of authors, publishers and booksellers involved in the publications of 18th-century books concerning Freemasonry with a particular focus on James Anderson (author).
Figure 4
Chronological distribution of the detected languages of the 53411 articles and books in the University of Szeged publication repository.
Figure 5
N-gram viewer. Distribution of “katolikus egyház” [Catholic church], “református egyház” [Reformed church], “evangélikus egyház” [Lutheran church] in the Délmagyarország daily newspaper, 1911–2009.
Figure 6
TagSphere analysis. Dan Brown’s novels. Keyword: god, word distance: 4 (shown in different colours), minimum word frequency: 7, lemmatized texts, stopwords removed.
Figure 7
The same TagSphere analysis as in Figure 6. Bar chart view with statistical data.
Figure 8
Lexical diversity metrics in J. K. Rowling’s Harry Potter novels.
Figure 9
Keyword-in-context. The word “magic” in J. K. Rowling’s Harry Potter and the Philosopher’s Stone.
Figure 10
Topic modelling of Dan Brown’s novels.
Figure 11
Topic modelling of the Szegedi Egyetem [University of Szeged] Magazin, 1953–2011.
Figure 12
Part-of-speech analysis in Dan Brown’s novels.
Figure 13
Part-of-speech analysis of J. K. Rowling’s Harry Potter novels. Statistical results.
Table 1
Named entity recognition in different languages.
Figure 14
Named entity recognition and linking in Dan Brown’s Da Vinci Code.