get_sentiment_tweets: get_sentiment_tweets

In TwitterAutomatedTrading: Automated Trading Using Tweets

Description

This function computes the sentiment from tweets. Remind to connect with twitter using your API Key.

Usage

get_sentiment_tweets(
  ntweets,
  time_tweet,
  terms_list,
  time_zone,
  positive_dictionary,
  negative_dictionary,
  sentiment_index_type
)

Arguments

ntweets	Number of tweets to be searched
time_tweet	Time in hours where the tweets will be filtered
terms_list	Terms to be searched
time_zone	The time zone
positive_dictionary	The list of positive terms of the dictionary
negative_dictionary	The list of negative terms of the dictionarya tibble with the words counting
sentiment_index_type	The sentiment type to be used according to the dictionary, positive, negative or both. Default is both, positive and negative

Value

A list with: (1) - the sentiment index, (2) a tibble with the words counting, (3) a tibble with the negative words counting and (4

Examples

## Not run: 
#Not run:
ntweets <- 500
time_tweet <- 6
terms_list <- c("IBOVESPA OR bovespa OR ibov OR petroleo OR $SPX OR $SPY OR $EWZ")
time_zone <- "Brazil/East"
positive_dictionary <- my_dictionary[['positive_terms']]
negative_dictionary <- my_dictionary[['negative_terms']]
sentiment_index <- get_sentiment_tweets(ntweets = ntweets,
terms_list = terms_list,
time_tweet = time_tweet,
time_zone = time_zone,
positive_dictionary = positive_dictionary,
negative_dictionary = negative_dictionary
)

sent_idx <- sentiment_index[[1]]
sent_wrd <- sentiment_index[[2]]
sent_pos <- sentiment_index[[3]]
sent_neg <- sentiment_index[[4]]

## End(Not run)

TwitterAutomatedTrading documentation built on July 1, 2020, 5:48 p.m.