Evidence map›Paper›PMID 33267178›Full record

ArticleEntropy (Basel, Switzerland)2019

Studying Lexical Dynamics and Language Change via Generalized Entropies: The Problem of Sample Size.

Alexander Koplenig, Sascha Wolfer, Carolin Müller-Spitzer

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Quebec French Action-Naming Database with Video Stimuli.Journal of psycholinguistic research · 2026
    Article
  2. Article
  3. Information Theory and Language.Entropy (Basel, Switzerland) · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alexander KoplenigDepartment of Lexical Studies, Institute for the German language (IDS), 68161 Mannheim, Germany.ORCID 0000-0002-9630-9680
Sascha WolferDepartment of Lexical Studies, Institute for the German language (IDS), 68161 Mannheim, Germany.
Carolin Müller-SpitzerDepartment of Lexical Studies, Institute for the German language (IDS), 68161 Mannheim, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, it was demonstrated that generalized entropies of order α offer novel and important opportunities to quantify the similarity of symbol sequences where α is a free parameter. Varying this parameter makes it possible to magnify differences between different texts at specific scales of the corresponding word frequency spectrum. For the analysis of the statistical properties of natural languages, this is especially interesting, because textual data are characterized by Zipf's law, i.e., there are very few word types that occur very often (e.g., function words expressing grammatical relationships) and many word types with a very low frequency (e.g., content words carrying most of the meaning of a sentence). Here, this approach is systematically and empirically studied by analyzing the lexical dynamics of the German weekly news magazine

Indexed as

generalized divergencegeneralized entropyJensen–Shannon divergencesample sizetext lengthZipf’s law

Identifiers

PMID33267178
PMCPMC7514953

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.