Text analysis with networks.
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Updated
May 8, 2024 - Python
Text analysis with networks.
Uso de structural topic modeling para análise de teses e dissertações da pós-graduação em filosofia no Brasil.
LinkOrgs: An R package for linking linking records on organizations using half a billion open-collaborated records from LinkedIn
Beautiful visualizations of how language differs among document types.
Literature 📄 and datasets 📚 on automatic populism detection
Summer/ winter schools, workshops and conferences in computational social science 🫂
A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).
A tool for Semantic Scaling of Political Text (branch of Topfish, a suite of tools for Political Text Analysis)
Material from my Machine Learning for the Social Sciences course
Interpretable data visualizations for understanding how texts differ at the word level
Collection of text corpora for publicly available speeches from Mexican president Andres Manuel Lopez Obrador (AMLO) sourced from YouTube. The dataset includes his daily morning conferences (conferencias mañaneras) 😴🪿
A little sample of my recent work as a data analyst.
The ABC of Computational Text Analysis. BA Seminar, Spring 2022, University of Lucerne
This is a designed package for replicating the estimates and findings in the article of Factionalism and the Red Guards under Mao's China: Ideal Point Estimation Using Text Data.
An Automation Webcrawler for Extracting Central Bankers' Speeches
This repository uses text-as-data methods alongside traditional primary source reading to analyze early American state constitutions. The R scripts create a function to scrape and clean the constitutional text, run sentiment analysis, calculate tf-idf, and perform LDA. This is a work-in-progress.
Empirical framework applied to parliament discourses and Twitter data, with a Discourse Polarization Index.
'dictvectoR' measures the similarity between a concept dictionary and documents, using fastText word vectors. Implements the "Distributed-Dictionary-Representation" (Garten et al. 2018) method in R.
Code and models for 3 different tools to measure appeals to 8 discrete emotions in German political text
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