Zipf's law of abbreviation as a language universal

By C. Bentz, Ramon Ferrer-i-Cancho. 2016

85 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cultural Studies, Molecular Biology, Natural Language Processing, Computational Linguistics & Semantics, Linguistics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Douwe Kiela
2. Mohit Bansal
3. Nazneen Rajani
4. Tristan Thrush
5. Yacine Jernite
6. Yejin Choi
7. Margaret Mitchell
8. Angelina McMillan-Major

In Cultural Studies

1. Douwe Kiela

In Molecular Biology

1. Douwe Kiela
2. Nazneen Rajani

In Natural Language Processing

1. Tristan Thrush
2. Douwe Kiela
3. Nazneen Rajani
4. Angelina McMillan-Major
5. Yacine Jernite
6. Alexandra Sasha Luccioni
7. Margaret Mitchell
8. Jason Aaron Edward Weston

In Computational Linguistics & Semantics

1. Douwe Kiela
2. Margaret Mitchell

In Linguistics

1. Douwe Kiela

Citations in the corpus

• Measuring Data (2022, background): “Natural human languages adhere to Zipf’s law to various extents, with different coefficients (Gelbukh and Sidorov, 2001; Bentz and Ferrer Cancho, 2016).”