SentimentPerTopic

Sentiment per topic calculation for italian text. Needs tm's DocumentTermMatrix and a sentences vector generated with syuzhet's get_sentences. The calculation is made with the sentixR package, while the topics are generated with topicmodels's lda and terms functions. In order to take into account only some of the given sentences, dplyr's filter function gets called.

USAGE

Parameters:

• dtm
        an object of class DocumentTermMatrix.
• sentences
        a character vector of sentences made with get_sentences.
• topic_number
        the number of topics to search for.
• words_pt
        number of words to consider relevant for each topic.
• seed
        seed used for the inizialization of VEM algorithm (implemented in lda).

spt(dtm, sentences, topic_number=5, words_pt=6, seed=0) #seed is used to initialize LDA 

RETURN VALUE

The functions returns a data.frame containing two columns, one containing the terms of each topic and one with the sentiment value.