Analysis of compatibility of the VMS with texts written in natural language.

Keywords found for the New Testament and for the Voyninch manuscript.

Analysis of compatibility of the VMS with shuffled texts.

Words with equal Combined Measures take equal ranks.

This compressed file contains the Matlab code that was used to query PubMed and to generate the figures of the paper. (ZIP)

Reddit comments from January 2017 to August 2018, related to the posts including in their title some keywords related with NGI topics.

Words with high degree of fractality are important words according to subject of the book and common words have low degree of fractality. The string un which is placed in the...

While the use of statistical physics methods to analyze large corpora has been useful to unveil many patterns in texts, no comprehensive investigation has been performed on the...

List of fundamental questions for identifying the nature of unknown manuscripts.

Reddit comments from January 2017 to August 2018, related to the posts including in their title some keywords related to NGI topics. Note that the month of March 2017 is not...

(PDF)

Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern power systems that include features such as conventional generators with...

Categories and examples of Weibo posts that led to a peak in Weibo traffic as found in the WeiboScope database (January 1 to December 31, 2012).

*Class A and B diseases require immediate notification to health authorities of a higher administrative level; Class C diseases require periodical notification. Class A refers...

General statistics for the dataset.

These words are important according to the subject of the book. The word, f is related to some classification of species such as f8, f10, f14, … and some proper names. f is kept...

Nv and Ng are the number of vocabulary words from the book and number of glossary words for each cut-off frequency, respectively.

Summary of start-up content analysis of YouTube (n = 32).

The top 10 largest and smallest β keywords.