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Software . 2021
License: CC BY NC
Data sources: ZENODO
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ZENODO
Software . 2021
License: CC BY NC
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
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Introduction to Cultural Analytics & Python

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 02 Jan 2021 English Publisher:Zenodo
Authors: Melanie Walsh;

doi: 10.5281/zenodo.4411251 , 10.5281/zenodo.4443809

Introduction to Cultural Analytics & Python

Abstract

The Introduction to Cultural Analytics & Python textbook offers an introduction to the programming language Python that is specifically designed for humanities students and scholars with no previous programming experience. It demonstrates how Python can be used to study cultural materials such as song lyrics, short stories, newspaper articles, tweets, Reddit posts, and film screenplays. It introduces computational methods such as web scraping, APIs, topic modeling, Named Entity Recognition (NER), network analysis, and mapping. Website: https://melaniewalsh.github.io/Intro-Cultural-Analytics/welcome.html

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Keywords

python, cultural analytics, digital humanities

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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