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Text analysis in Python for social scientists = discovery and exploration /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Text analysis in Python for social scientists/ Dirk Hovy.
Reminder of title:	discovery and exploration /
Author:	Hovy, Dirk.
Published:	Cambridge :Cambridge University Press, : 2020.,
Description:	95 p. :ill., digital ;23 cm.
Notes:	Title from publisher's bibliographic system (viewed on 11 Jan 2021).
Subject:	Social sciences - Research -
Online resource:	https://doi.org/10.1017/9781108873352
ISBN:	9781108873352

Text analysis in Python for social scientists = discovery and exploration /
Hovy, Dirk.

Text analysis in Python for social scientistsdiscovery and exploration /[electronic resource] :Dirk Hovy. - Cambridge :Cambridge University Press,2020. - 95 p. :ill., digital ;23 cm. - Cambridge elements. Elements in quantitative and computational methods for the social sciences,2398-4023. - Cambridge elements.Elements in quantitative and computational methods for the social sciences..

Title from publisher's bibliographic system (viewed on 11 Jan 2021).

Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.

ISBN: 9781108873352Subjects--Topical Terms:

524282
Social sciences
--Research

LC Class. No.: H62 / .H69 2020

Dewey Class. No.: 300.72

Text analysis in Python for social scientists = discovery and exploration /
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245 1 0 $a Text analysis in Python for social scientists $h [electronic resource] : $b discovery and exploration / $c Dirk Hovy.
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500 $a Title from publisher's bibliographic system (viewed on 11 Jan 2021).
520 $a Text is everywhere, and it is a fantastic resource for social scientists. However, because it is so abundant, and because language is so variable, it is often difficult to extract the information we want. There is a whole subfield of AI concerned with text analysis (natural language processing). Many of the basic analysis methods developed are now readily available as Python implementations. This Element will teach you when to use which method, the mathematical background of how it works, and the Python code to implement it.
650 0 $a Social sciences $x Research $x Methodology. $3 524282
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830 0 $a Cambridge elements. $p Elements in quantitative and computational methods for the social sciences. $3 3729224
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