Text Mining

This repository has the analysis that was did for 3 politicians from Rio de Janeiro using their tweets.

The paper is published and can be downloaded at this url: https://periodicos.uff.br/anaisdoser/article/view/29333.

That was the following steps for the text analysis:

Twitter

Using the social network API (package twitteR), get tweets from users.

Manipulate data

1. To lower
2. Tokenization
3. Remove punctuation
4. Remove stopwords
5. Stem (to join with the sentimental lexicon)

Sentimental Analysis

Using sentiLex_lem_PT02 dictionary

TF-IDF

Identify importants terms to each poltician. This technique consider the term frequency and the inverse document frequency.

Topic Modelling

We used the LDA (Latent Dirichlet Allocation) algorithm to build a model to predict each tweet and classify them into a group.