Evaluating Topic Models in Portuguese Political Comments About Bills from Brazil’s Chamber of Deputies

• Nádia F. F. da Silva USP / UFG
• Marília Costa R. Silva USP
• Fabíola S. F. Pereira USP / UFU
• João Pedro M. Tarrega USP
• João Vitor P. Beinotti USP
• Márcio Fonseca Câmara dos Deputados
• Francisco Edmundo de Andrade Câmara dos Deputados
• André C. P. de L. F. de Carvalho Câmara dos Deputados

Resumo

The popular participation in Law-making is an important resource in the evolution of Democracy and Direct Legislation. The amount of legislative documents produced within the past decade has risen dramatically, making it difficult for law practitioners to attend to legislation and still listen to the opinion of the citizens. This work focuses on the use of topic models for summarizing and visualizing Brazilian comments about legislation (bills). In this paper, we provide a qualitative evaluation from a legal expert and compare it with the topics predicted by our model. For such, we designed a specific sentence embedding technique able to induce models for Portuguese texts, and we used these models as topic model, obtaining very good results. We experimentally compared our proposal with other techniques for multilingual sentence embeddings, evaluating them in three topical corpora prepared by us, two of them annotated by a specialist and the other automatically annotated by hashtags.

Palavras-chave: Topic models, Language models, Natural language processing, Sentence embeddings