Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts

Gabriel L Recchia, Max M Louwerse

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.

    Original languageEnglish
    JournalCognitive Science
    DOIs
    Publication statusPublished - 2015

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    Computational linguistics
    Linguistics
    Excavation
    Artifacts
    Statistics
    Computational methods
    Civilization
    Names

    Cite this

    @article{15f77b55b7744d7ca931f9f46e3102c3,
    title = "Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts",
    abstract = "Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.",
    author = "Recchia, {Gabriel L} and Louwerse, {Max M}",
    note = "Copyright {\circledC} 2015 Cognitive Science Society, Inc.",
    year = "2015",
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    language = "English",
    journal = "Cognitive Science",
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    Archaeology Through Computational Linguistics : Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts. / Recchia, Gabriel L; Louwerse, Max M.

    In: Cognitive Science, 2015.

    Research output: Contribution to journalArticleScientificpeer-review

    TY - JOUR

    T1 - Archaeology Through Computational Linguistics

    T2 - Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts

    AU - Recchia, Gabriel L

    AU - Louwerse, Max M

    N1 - Copyright © 2015 Cognitive Science Society, Inc.

    PY - 2015

    Y1 - 2015

    N2 - Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.

    AB - Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.

    U2 - 10.1111/cogs.12311

    DO - 10.1111/cogs.12311

    M3 - Article

    C2 - 26467321

    JO - Cognitive Science

    JF - Cognitive Science

    SN - 0364-0213

    ER -