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Large language models and political science

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A377THBJ9" target="_blank" >RIV/00216208:11320/23:377THBJ9 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.frontiersin.org/articles/10.3389/fpos.2023.1257092/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fpos.2023.1257092/full</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3389/fpos.2023.1257092" target="_blank" >10.3389/fpos.2023.1257092</a>

Alternative languages

  • Result language

    ruština

  • Original language name

    Large language models and political science

  • Original language description

    "Large Language Models (LLMs) are a type of artificial intelligence that uses information from very large datasets to model the use of language and generate content. While LLMs like GPT-3 have been used widely in many applications, the recent public release of OpenAI's ChatGPT has opened more debate about the potential uses and abuses of LLMs. In this paper, we provide a brief introduction to LLMs and discuss their potential application in political science and political methodology. We use two examples of LLMs from our recent research to illustrate how LLMs open new areas of research. We conclude with a discussion of how researchers can use LLMs in their work, and issues that researchers need to be aware of regarding using LLMs in political science and political methodology."

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>ost</sub> - Miscellaneous article in a specialist periodical

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    "Frontiers in Political Science"

  • ISSN

    2673-3145

  • e-ISSN

  • Volume of the periodical

    5

  • Issue of the periodical within the volume

    2023-10-16

  • Country of publishing house

    RU - RUSSIAN FEDERATION

  • Number of pages

    12

  • Pages from-to

    1-12

  • UT code for WoS article

  • EID of the result in the Scopus database