Dataset origin: https://lrec2020.lrec-conf.org/sharedlrs2020/584_res_1.txt

Description

This is a new database for computational approaches of synchronized diachronic investigation of language pairs, and subsequent novel findings stemming from the cognates temporal comparison of the two chosen languages. The present study is the first in the literature to use computational approaches and large data to make a cross-language temporal analysis. Taken and computed from google n-grams, a cognate database was constructed with 492 English-French word pairs composed of nouns, adjectives and adverbs. Each pair has between one and four forms in English, and up to ten in French. In English, most words have only one form for adjectives and adverbs, while most nouns have two forms (singular and plural). In French, with masculine and feminine, singular and plural, most nouns and adjectives can be found in four different surface forms.

Citation

@inproceedings{frossard-etal-2020-dataset,
    title = "Dataset for Temporal Analysis of {E}nglish-{F}rench Cognates",
    author = "Frossard, Esteban  and
      Coustaty, Mickael  and
      Doucet, Antoine  and
      Jatowt, Adam  and
      Hengchen, Simon",
    editor = "Calzolari, Nicoletta  and
      B{\'e}chet, Fr{\'e}d{\'e}ric  and
      Blache, Philippe  and
      Choukri, Khalid  and
      Cieri, Christopher  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Isahara, Hitoshi  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, H{\'e}l{\`e}ne  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
    month = may,
    year = "2020",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2020.lrec-1.107",
    pages = "855--859",
    abstract = "Languages change over time and, thanks to the abundance of digital corpora, their evolutionary analysis using computational techniques has recently gained much research attention. In this paper, we focus on creating a dataset to support investigating the similarity in evolution between different languages. We look in particular into the similarities and differences between the use of corresponding words across time in English and French, two languages from different linguistic families yet with shared syntax and close contact. For this we select a set of cognates in both languages and study their frequency changes and correlations over time. We propose a new dataset for computational approaches of synchronized diachronic investigation of language pairs, and subsequently show novel findings stemming from the cognate-focused diachronic comparison of the two chosen languages. To the best of our knowledge, the present study is the first in the literature to use computational approaches and large data to make a cross-language diachronic analysis.",
    language = "English",
    ISBN = "979-10-95546-34-4",
}