Case study · NLP, Central European University · 2026

How Dominicans talk about Haitian migration: an NLP study of speeches and Reddit

In 2023, as an intern at the Organization of American States office in Santo Domingo, I wrote a report on Dominican identity and migration. At CEU I rebuilt it as a text-analysis project: 43 presidential speeches and about 8,800 Reddit sentences, read with topic models, clustering and a Spanish transformer for sentiment.

Course: Text Analysis & NLP, CEU
Corpus: 6,804 speech + ~8,800 Reddit sentences
Methods: Seeded LDA · DBSCAN · RoBERTuito

The question

How is Haitian migration framed in Dominican public debate, from the presidency and from ordinary users online? I tested two hypotheses: sentences that use migration vocabulary carry more negative sentiment than other sentences, and the Reddit discussion clusters around security and negative framing.

Data

Presidential speeches: 43 speeches by Luis Abinader, scraped from presidencia.gob.do, August 2020 to February 2026. That gives 6,804 sentences.
Reddit: about 8,800 sentences from r/Dominicanos, pre-filtered for migration terms.
Context: official migration statistics for 2018 to 2023, and the ENI 2017 immigrant survey, which counted 570,933 foreign-born residents, 5.6% of the population.

Method

The pipeline is in R with quanteda. Frequency trimming usually removes rare words, and in migration debates some of the most loaded terms are rare, so I kept a whitelist of about 40 of them. Then:

Seeded LDA with six topics, five of them seeded from theory, and an unseeded LDA as a validation check.
DBSCAN on a TF-IDF matrix reduced with SVD (minPts = 30), to find clusters without fixing their number in advance.
Sentiment from RoBERTuito (pysentimiento), a Spanish transformer trained on social media, called from R through reticulate.

Results

The two sources have very different overall tone. Speech sentences are 40.0% positive, 46.8% neutral and 13.2% negative. Reddit sentences are 7.4% positive, 44.5% neutral and 48.1% negative.

In speeches, the 251 migration sentences have a mean negativity of 0.432 against 0.386 for the rest: 4.6 points more negative.
On Reddit, the 1,518 migration sentences score 0.763 against 0.657: 10.6 points more negative.
Reddit users write words starting with hait- 25.3 times per 1,000 tokens. The presidency does so 1.5 times.
The most negative terms are indocumentado (0.81) and deportación (0.78). The Haiti-migration topic is the most negative topic (0.75).
Haiti vocabulary shows up in four of the six unseeded topics, and in at least four of the six DBSCAN clusters.

Both hypotheses hold. Migration language is more negative than other language in both corpora, and Haiti dominates the online conversation far more than it does the president's speeches.

Code

Scraping, cleaning, topic models and sentiment scoring are on GitHub: dialectical_identity_in_RD.