The ABC of Computational Text Analysis. BA Seminar, Spring 2022, University of Lucerne

A small showcase for topic modeling with the tmtoolkit Python package. I use a corpus of articles from the German online news website Spiegel Online (SPON) to create a topic model for before and during the COVID-19 pandemic.

Original corpus of articles relating to refugees scraped from Tennessee newspaper The Chattanoogan along with simple code for text-as-data word cloud.

Empirical framework applied to parliament discourses and Twitter data, with a Discourse Polarization Index.

Material from my Machine Learning for the Social Sciences course

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

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.

Uso de structural topic modeling para análise de teses e dissertações da pós-graduação em filosofia no Brasil.

From using xpdf, rvest, and quanteda on United Nations Digital Library search results to applying dictionaries to speeches in United Nations meeting records

Literature 📄 and datasets 📚 on automatic populism detection

The ABC of Computational Text Analysis. BA Seminar, Spring 2021, University of Lucerne

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.

Code and models for 3 different tools to measure appeals to 8 discrete emotions in German political text

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

A tutorial on using regular expressions in R

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

An Automation Webcrawler for Extracting Central Bankers' Speeches

Code for estimating word embeddings with gensim in R.

'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.