Rank Diversity of Languages: Generic Behavior in Computational Linguistics
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{"title"=>"Rank diversity of languages: Generic behavior in computational linguistics", "type"=>"journal", "authors"=>[{"first_name"=>"Germinal", "last_name"=>"Cocho", "scopus_author_id"=>"55989696100"}, {"first_name"=>"Jorge", "last_name"=>"Flores", "scopus_author_id"=>"7202519734"}, {"first_name"=>"Carlos", "last_name"=>"Gershenson", "scopus_author_id"=>"56002726000"}, {"first_name"=>"Carlos", "last_name"=>"Pineda", "scopus_author_id"=>"12544676000"}, {"first_name"=>"Sergio", "last_name"=>"Sánchez", "scopus_author_id"=>"7202745337"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"604108740", "sgr"=>"84928922871", "issn"=>"19326203", "pmid"=>"25849150", "scopus"=>"2-s2.0-84928922871", "doi"=>"10.1371/journal.pone.0121898"}, "id"=>"9f703881-fdbd-3123-bc4d-6d20c5b39717", "abstract"=>"Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.", "link"=>"http://www.mendeley.com/research/rank-diversity-languages-generic-behavior-computational-linguistics", "reader_count"=>31, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>2, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>2, "Professor"=>5}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>2, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Master"=>4, "Other"=>1, "Student > Bachelor"=>5, "Lecturer"=>2, "Professor"=>5}, "reader_count_by_subject_area"=>{"Engineering"=>1, "Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>1, "Materials Science"=>1, "Mathematics"=>4, "Agricultural and Biological Sciences"=>5, "Physics and Astronomy"=>6, "Psychology"=>1, "Social Sciences"=>2, "Computer Science"=>5, "Decision Sciences"=>1, "Linguistics"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Materials Science"=>{"Materials Science"=>1}, "Social Sciences"=>{"Social Sciences"=>2}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>6}, "Psychology"=>{"Psychology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>5}, "Computer Science"=>{"Computer Science"=>5}, "Linguistics"=>{"Linguistics"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"United States"=>2, "United Kingdom"=>1, "Mexico"=>1, "Germany"=>1, "Spain"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2007940"], "description"=>"<div><p>Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution <i>rank diversity</i>. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.</p></div>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369726, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898", "stats"=>{"downloads"=>18, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_Diversity_of_Languages_Generic_Behavior_in_Computational_Linguistics_/1369726", "title"=>"Rank Diversity of Languages: Generic Behavior in Computational Linguistics", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007937"], "description"=>"<p>Blue dots show rank diversity, windowed in the red line. The black line shows the sigmoid fit with <i>μ</i> = 1.24 and <i>σ</i> = 0.76. The green line shows a simulation with </p><p></p><p></p><p><mi>σ</mi><mo>^</mo></p><mo>=</mo><mn>0</mn><mo>.</mo><mn>18</mn><p></p><p></p>. Notice that there is no head as <i>μ</i>−2<i>σ</i> < 0. This is to be expected, as many players enter and leave the ranking during the years considered.<p></p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369723, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g007", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_diversity_of_male_chess_players_obtained_from_the_trimestral_FIDE_rankings_from_April_2001_to_May_2012_t_50_considering_the_first_10_000_ranks_/1369723", "title"=>"Rank diversity of male chess players obtained from the trimestral FIDE rankings from April, 2001 to May, 2012 (Δ<i>t</i> = 50), considering the first 10,000 ranks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007931"], "description"=>"<p>Head words have <i>k</i> ≤ <i>k</i><sub>−</sub>, body words have <i>k</i><sub>−</sub> < <i>k</i> ≤ <i>k</i><sub>+</sub>, and tail words have <i>k</i><sub>+</sub> < <i>k</i>. See <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121898#pone.0121898.g002\" target=\"_blank\">Fig. 2</a> for color coding.</p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369717, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g003", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evolution_in_time_of_the_center_of_the_sigmoid_middle_panel_and_the_borders_of_the_head_and_body_bottom_panel_and_body_and_tail_top_panel_for_the_different_languages_along_time_for_intervals_of_fifty_years_i_e_t_50_/1369717", "title"=>"Evolution in time of the center of the sigmoid (middle panel), and the borders of the head and body (bottom panel) and body and tail (top panel) for the different languages along time for intervals of fifty years, <i>i.e.</i> Δ<i>t</i> = 50.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007930"], "description"=>"<p>Diversity <i>d</i> as a function of the rank <i>k</i> for different languages from 1800 to 2008, where <i>d</i>(<i>k</i>) measures how many different words appear for a given rank <i>k</i> during the time considered (Δ<i>t</i> = 208). For example, for English, <i>d</i>(1) = 1/208, as the word ‘the’ appears in the first rank for all years considered. Although we have analyzed up to <i>k</i> ≈ 10<sup>6</sup>, rank diversity for <i>k</i> > 10<sup>4</sup> is not shown as <i>d</i>(<i>k</i>) ≈ 1, <i>i.e.</i>, a different word appears in each rank every year. Data are windowed over time, with a slot of size <i>δ</i>log<sub>10</sub><i>k</i> = 0.1, for the sake of clearness. Additionally, the sigmoid defined in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121898#pone.0121898.e001\" target=\"_blank\">Equation 1</a> is shown as a black dashed curve, with the best fit parameters, also reported in each subfigure. The mean square error <i>e</i> between the data and the fit, is also given. The shaded region corresponds to the average “body” of all languages.</p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369716, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g002", "stats"=>{"downloads"=>4, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_diversity_/1369716", "title"=>"Rank diversity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007935"], "description"=>"<p>The green curve represents the diversity corresponding to the language dynamics of a single realization of the Gaussian random walk model. We also include data for all languages studied, but normalized so that <i>k</i><sub>±</sub> coincide. The ansatz for the rank diversity is plotted as a parameter-free cumulative of a Gaussian with zero mean and unit variance as a dashed black curve.</p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369721, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g006", "stats"=>{"downloads"=>2, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_diversity_for_the_simulated_language_/1369721", "title"=>"Rank diversity for the simulated language.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007933"], "description"=>"<p>[a]: Evolution of the rank for several particular, but random words in different regimes in the English language. From bottom to top we show words with initial ranks of order 1 (head), 100 (body) and 1000 (tail). [b]: Evolution of the rank for several particular, but random words in different regimes, for our scale-free Gaussian walker, i.e. the simulated language we have generated.</p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369719, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g004", "stats"=>{"downloads"=>2, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_evolution_/1369719", "title"=>"Rank evolution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007934"], "description"=>"<p>Notice that for words in the head, the granularity of the model (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121898#pone.0121898.e004\" target=\"_blank\">Equation 3</a>) shows up as large deviations from the Gaussian. For the body and tail, the relative jumps are similar independently of the initial rank of the word. We also show, as a thick green curve, the Lorentzian distribution which best fits the average of the curves for the body and tail. A Gaussian, with zero mean and the most common standard deviation </p><p></p><p></p><p><mi>σ</mi><mo>^</mo></p><mo>=</mo><mn>0</mn><mo>.</mo><mn>0575</mn><p></p><p></p>, is also shown in red for comparison (see text for details). The corresponding plot for other languages is shown in the supplementary information.<p></p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369720, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g005", "stats"=>{"downloads"=>1, "page_views"=>27, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_relative_size_of_frequency_changes_k_t_1_k_t_k_t_in_the_case_of_English_for_words_in_the_head_gold_that_start_with_rank_between_1_and_10_the_body_blue_rank_between_200_and_210_and_the_tail_green_rank_between_5000_and_5010_/1369720", "title"=>"Distribution of relative size of frequency changes [<i>k</i><sub><i>t</i>+1</sub>−<i>k</i><sub><i>t</i></sub>]/<i>k</i><sub><i>t</i></sub> in the case of English for words in the head (gold) (that start with rank between 1 and 10), the body (blue) (rank between 200 and 210), and the tail (green) (rank between 5000 and 5010).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}
  • {"files"=>["https://ndownloader.figshare.com/files/2007929"], "description"=>"<p>When words have more than one meaning, the first sense, according to Google Translate, was used. The color code for languages is as follows: light blue for French, green for German, yellow for Italian, dark blue for Spanish, and dark orange for Russian. Additionally, light orange will be used for English when required (see also <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0121898#pone.0121898.g002\" target=\"_blank\">Fig. 2</a>). The same color coding for languages will be used throughout the rest of the article.</p>", "links"=>[], "tags"=>["distribution rank diversity", "word ranks change", "Computational Linguistics Statistical studies", "lognormal distribution"], "article_id"=>1369715, "categories"=>["Biological Sciences", "Science Policy"], "users"=>["Germinal Cocho", "Jorge Flores", "Carlos Gershenson", "Carlos Pineda", "Sergio Sánchez"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0121898.g001", "stats"=>{"downloads"=>2, "page_views"=>24, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overlap_of_the_20_most_frequent_words_continuous_lines_and_of_the_20_most_frequent_content_words_dashed_lines_across_languages_with_respect_to_English_as_a_function_of_time_/1369715", "title"=>"Overlap of the 20 most frequent words (continuous lines), and of the 20 most frequent <i>content</i> words (dashed lines) across languages, with respect to English, as a function of time.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-04-07 04:04:00"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
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  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"9", "full-text"=>"11", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"8", "full-text"=>"8", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
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Relative Metric

{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}
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