The Giver: A Corpus-Based Analysis of Word Frequencies

A translator is seen to leave a personal mark on the text through their stylistic choices and the patterns formed by these choices. This article comprises a case study that uses a specialized comparative corpus containing translations of C.P. Cavafy's canon in order to explore the distinctive stylistic features of Rae Dalven and of Edmund Keeley and Philip Sherrard (working in collaboration), in both quantitative and qualitative terms. Exploring the different approaches to Cavafy's poetry on the stylistic level reveals the stylistic fragmentation of the poet after crossing over into a dominant language and literary market.Overall word frequencies for each translation are examined, the stylistic features that are prominent in each case are identified, and their significance is considered. Special attention is also paid to the way a stylistic feature belonging to the ‘universal aspects of literature’ is treated by each translator. By foregrounding the translators and their distinct choices, the “homogenization” effects that often characterize translation into a major language are arrested. Instead, the focus falls on the factors that shape each translator's use of language and their impact.

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Statistical Analysis of Word Frequency Distribution in Lithuanian Texts of Different Genres

Lietuvos statistikos darbai ◽

10.15388/ljs.2016.13868 ◽

2016 ◽

Vol 55 (1) ◽

pp. 61-69

Author(s):

Neringa Bružaitė ◽

Tomas Rekašius

Keyword(s):

Statistical Analysis ◽

Word Frequency ◽

Frequency Distribution ◽

Hierarchical Clustering ◽

Distance Measure ◽

Structural Type ◽

Clustering Method ◽

Jaccard Distance ◽

Word Frequencies ◽

Word Frequency Distribution

The paper examines Lithuanian texts of different authors and genres. The main points ofinterest – the number of words, the number of different words and word frequencies. Structural type distributionand Zipf’s law are applied for describing the frequency distribution of words in the text. It is obvious that thelexical diversity of any text can be defined by different words that are used in the text, also called vocabulary.It is shown that the information contained in a reduced vocabulary is enough for dividing the texts analyzedin this article into groups by genre and author using a hierarchical clustering method. In this case, distancesbetween clusters are measured using the Jaccard distance measure, and clusters are aggregated using the Wardmethod.

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Linking Norms, Ratings, and Relations of Words and Concepts Across Multiple Language Varieties

10.31234/osf.io/tgw3z ◽

2020 ◽

Author(s):

Annika Tjuka ◽

Robert Forkel ◽

Johann-Mattis List

Keyword(s):

Web Application ◽

Age Of Acquisition ◽

Data Curation ◽

Data Sets ◽

Data Types ◽

Word Meanings ◽

Language Varieties ◽

Diverse Data ◽

Multiple Languages ◽

Word Frequencies

Psychologists and linguists have collected a great diversity of data for word and concept properties. In psychology, many studies accumulate norms and ratings such as word frequencies or age-of-acquisition often for a large number of words. Linguistics, on the other hand, provides valuable insights into relations of word meanings. We present a collection of those data sets for norms, ratings, and relations that cover different languages: ‘NoRaRe.’ To enable a comparison between the diverse data types, we established workflows that facilitate the expansion of the database. A web application allows convenient access to the data (https://digling.org/norare/). Furthermore, a software API ensures consistent data curation by providing tests to validate the data sets. The NoRaRe collection is linked to the database curated by the Concepticon project (https://concepticon.clld.org) which offers a reference catalog of unified concept sets. The link between words in the data sets and the Concepticon concept sets makes a cross-linguistic comparison possible. In three case studies, we test the validity of our approach, the accuracy of our workflow, and the applicability of our database. The results indicate that the NoRaRe database can be applied for the study of word properties across multiple languages. The data can be used by psychologists and linguists to benefit from the knowledge rooted in both research disciplines.

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Values and Estimation of Word Frequencies

Psychological Reports ◽

10.2466/pr0.1972.31.1.47 ◽

1972 ◽

Vol 31 (1) ◽

pp. 47-56 ◽

Cited By ~ 2

Author(s):

Thomas W. Milburn ◽

Nancy Bell

Keyword(s):

Social Desirability ◽

Frequency Of Occurrence ◽

Social Desirability Scale ◽

Initial Sample ◽

Actual Frequency ◽

A Value ◽

Word Classification ◽

Word Frequencies

It was hypothesized that people scoring high on a value or need such as evaluative dependence (measured by the Marlowe-Crowne Social Desirability Scale, M-C SD) would be more sensitive to words relevant to this need than would low scoring Ss and thus would tend to overestimate the frequency of occurrence of the need-relevant words. Words chosen for frequency ratings varied on a good-bad dimension pertaining to human characteristics or behaviors, and appropriate word classification was determined by the evaluative ratings of an initial sample of Ss. Words within each category were also matched for actual frequency of occurrence according to Thorndike-Lorge counts. The results did not support the hypothesis since high and low M-C SD scorers did not differ in their frequency ratings. The major finding, replicated in a second experiment, was that all Ss rated evaluative words as occurring more frequently than neutral words, even though the actual frequency of occurrence of the word types was the same.

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Computational Rules for Binary Word Frequencies of Occurrence

Recognition of Patterns ◽

10.1007/978-3-7091-4103-8_3 ◽

1974 ◽

pp. 91-109

Author(s):

Peter W. Becker

Keyword(s):

Binary Word ◽

Word Frequencies

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Network analysis as a method of assessing terms in a dataset comprising eating disorders

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.7.11079 ◽

2018 ◽

Vol 7 (2.7) ◽

pp. 841

Author(s):

Dr Adimulam Yesu Babu ◽

Dr Deepak Nedunuri ◽

T Venkata Sai Krishna

Keyword(s):

Eating Disorders ◽

Network Analysis ◽

Clustering Algorithm ◽

Agglomerative Hierarchical Clustering ◽

Network Graph ◽

Undirected Network ◽

Ward Clustering ◽

R Programming ◽

Network Centralities ◽

Word Frequencies

Eating disorders are central reason of physical and psycho-social morbidity. Several factors have been identified as being associated with the prevalence and progression of eating disorders in humans. Scientific investigation was carried out to assess the usage of terms in manuscript titles of nearly 900 published articles followed by network analysis and network centralities using R programming. The tm package, term document matrix function was utilized to create a term document matrix (TDM) from the corpus. A binary word matrix comprising 17 terms was created based on higher probability of occurring a term in a column. An agglomerative hierarchical clustering technique using ward clustering algorithm was presented. A data frame from the TDM was created to store data and used to plot word cloud based on word frequencies. An undirected network graph was plotted based on terms that appeared in the term matrix. Centralization measures such as Degree centrality, Closeness, Eigenvector and betweenness Centrality were reported.

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Observation of a Most Phenomenal Computed Calligraphy in Quran

Computer and Information Science ◽

10.5539/cis.v9n3p42 ◽

2016 ◽

Vol 9 (3) ◽

pp. 42

Author(s):

Baback Khodadoost

Keyword(s):

Present Article ◽

Recent Article ◽

Mathematical Structure ◽

Font Size ◽

Computational Structure ◽

The Given ◽

Word Frequencies ◽

Mathematical Design

<span style="font-size: 10pt; font-family: 'Times New Roman','serif'; color: black; mso-bidi-font-size: 9.0pt; mso-fareast-font-family: 宋体; mso-themecolor: text1; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">Observation of a multifaceted mathematical-computational structure of Quran through analysis of its letter and word frequencies and important implications of such observations have been extensively explained and discussed in a recent article: <span style="font-size: 10pt; font-family: 'Times New Roman','serif'; color: black; mso-bidi-font-size: 8.0pt; mso-fareast-font-family: 宋体; mso-themecolor: text1; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">“Khodadoost B. (2015) The Computed Scripture: Exponentially Based Fourier Regulated Construct of Quran and its fundamentally important Consequences"<span style="font-size: 10pt; font-family: 'Times New Roman','serif'; color: black; mso-bidi-font-size: 9.0pt; mso-fareast-font-family: 宋体; mso-themecolor: text1; mso-font-kerning: 1.0pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;" lang="EN-US">. In the present article we report observation of yet another facet of this mathematical structure of Quran which is a phenomenal "parametric name-printing”. This observation has been made through a systematic compute-plot algorithm which uses the given name and chapter frequencies of letters in Quran as its input and shows in the output, calligraphic printing in Arabic of the same name. Several names of God, Major Prophets, and even some physicists are shown to clearly manifest these calligraphic effects. Sensitivities of these observations to changes in letter frequencies in Quran are so high that increase or decrease of even one letter and only in one chapter of Quran can completely demolish the calligraphic effects. These astonishing observations not only are extremely important and interesting in their own right, but also point to an immensely complicated and intricate super-intelligent mathematical design of Quran and reinforce "Mathematically Fully constrained Writing" or MFCW identity of this scripture and its consequences, as have been explained in the above article.

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