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text-as-data
Here are 10 public repositories matching this topic...
Notebooks for the Seattle PyData 2017 talk on Scattertext
visualization
nlp
natural-language-processing
word2vec
pydata
political-science
gender
political-parties
computational-social-science
text-visualization
text-as-data
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Updated
Jan 12, 2018 - HTML
Interpretable data visualizations for understanding how texts differ at the word level
natural-language-processing
sentiment-analysis
information-theory
text-analysis
data-visualization
digital-humanities
computational-social-science
text-as-data
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Updated
Jul 9, 2020 - Python
Automated text analysis with networks.
visualization
nlp
sociology
text-analysis
network-analysis
computational-social-science
text-as-data
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Updated
Jul 9, 2020 - Python
A tool for Semantic Scaling of Political Text (branch of Topfish, a suite of tools for Political Text Analysis)
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Updated
Oct 7, 2019 - Python
2018 Computational Text Analysis Notebooks, University of Mannheim
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Updated
Nov 22, 2018 - Jupyter Notebook
Summer 2017 Social Media Analytics Workshop Series
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Updated
May 19, 2018 - HTML
From using xpdf, rvest, and quanteda on United Nations Digital Library search results to applying dictionaries to speeches in United Nations meeting records
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Updated
Apr 16, 2019 - R
Original corpus of articles relating to refugees scraped from Tennessee newspaper The Chattanoogan along with simple code for text-as-data word cloud.
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Updated
Nov 11, 2019 - R
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Hi there,
I think there might be a mistake in the documentation. The
Understanding Scaled F-Scoresection saysThe F-Score of these two values is defined as:
$$ \mathcal{F}_\beta(\mbox{prec}, \mbox{freq}) = (1 + \beta^2) \frac{\mbox{prec} \cdot \mbox{freq}}{\beta^2 \cdot \mbox{prec} + \mbox{freq}}. $$
$\beta \in \mathcal{R}^+$ is a scaling factor where frequency is favored if $\beta