PhD in Economics Empirical Research Course

Beautiful visualizations of how language differs among document types.

Code for collecting and cleaning speeches (text) of the US 2020 election campaign. Corresponding publication: "A text dataset of campaign speeches of the main tickets in the 2020 US presidential election", by Ioannis Chalkiadakis, Louise Anglès d’Auriac, Gareth W. Peters, and Divina Frau-Meigs

Summer/ winter schools, workshops and conferences in computational social science 🫂

LinkOrgs: An R package for linking linking records on organizations using half a billion open-collaborated records from LinkedIn

Replication script for the Webscrapping Transcripts of the Parliamentary Debates in the National Council of the Slovak Republic (1994-2023) and the ensuing sentiment analysis

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) 😴🪿

Interpretable data visualizations for understanding how texts differ at the word level

Text analysis with networks.

Literature 📄 and datasets 📚 on automatic populism detection

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

🇮🇱🇵🇸 News coverage of Israel-Hamas War 🇵🇸🇮🇱

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.