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New model suggests stopwords deviate from Zipf's law

By PulseAugur Editorial · [1 sources] ·

A new research paper proposes that the distribution of stopwords and function words in language deviates from Zipf's law, instead fitting a Beta Rank Function (BRF). The study suggests that non-stopwords and non-function words also deviate from Zipf's law, but are better described by a quadratic function of log-token-count over log-rank. The researchers developed a stopword/function word/subset selection model based on word rank, which they validated with independent text collections and demonstrated analytically to explain the observed rank-frequency distributions. AI

RANK_REASON The cluster contains an academic paper detailing a new linguistic distribution model. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CL →

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New model suggests stopwords deviate from Zipf's law

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The cluster contains an academic paper detailing a new linguistic distribution model. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Wentian Li, Oscar Fontanelli ·

    Non-Zipfian Distribution of Stopwords or Function Words and Subset Selection Models

    arXiv:2603.04691v2 Announce Type: replace Abstract: Stopwords and function words are relatively less informative for the content of a language and more often play a structural role in a sentence. Stopwords are ubiquitous words and may contain verbs, adjectives and adverbs. On the…

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