as.sentiment: Convert a sentiment table to a sentiment object

In sentometrics: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction

Description

Converts a properly structured sentiment table into a sentiment object, that can be used for further aggregation with the aggregate.sentiment function. This allows to start from sentiment scores not necessarily computed with compute_sentiment.

Usage

as.sentiment(s)

Arguments

s

a data.table or data.frame that can be converted into a sentiment object. It should have at least an "id", a "date", a "word_count" and one sentiment scores column. If other column names are provided with a separating "--", the first part is considered the lexicon (or more generally, the sentiment computation method), and the second part the feature. For sentiment column names without any "--", a "dummyFeature" component is added.

Value

A sentiment object.

Author(s)

Samuel Borms

Examples

set.seed(505)

data("usnews", package = "sentometrics")
data("list_lexicons", package = "sentometrics")

ids <- paste0("id", 1:200)
dates <- sample(seq(as.Date("2015-01-01"), as.Date("2018-01-01"), by = "day"), 200, TRUE)
word_count <- sample(150:850, 200, replace = TRUE)
sent <- matrix(rnorm(200 * 8), nrow =  200)
s1 <- s2 <- data.table::data.table(id = ids, date = dates, word_count = word_count, sent)
s3 <- data.frame(id = ids, date = dates, word_count = word_count, sent,
                 stringsAsFactors = FALSE)
s4 <- compute_sentiment(usnews$texts[201:400],
                        sento_lexicons(list_lexicons["GI_en"]),
                        "counts", do.sentence = TRUE)
m <- "method"

colnames(s1)[-c(1:3)] <- paste0(m, 1:8)
sent1 <- as.sentiment(s1)

colnames(s2)[-c(1:3)] <- c(paste0(m, 1:4, "--", "feat1"), paste0(m, 1:4, "--", "feat2"))
sent2 <- as.sentiment(s2)

colnames(s3)[-c(1:3)] <- c(paste0(m, 1:3, "--", "feat1"), paste0(m, 1:3, "--", "feat2"),
                           paste0(m, 4:5))
sent3 <- as.sentiment(s3)

s4[, "date" := rep(dates, s4[, max(sentence_id), by = id][[2]])]
sent4 <- as.sentiment(s4)

# further aggregation from then on is easy...
sentMeas1 <- aggregate(sent1, ctr_agg(lag = 10))
sent5 <- aggregate(sent4, ctr_agg(howDocs = "proportional"), do.full = FALSE)

sentometrics documentation built on Aug. 18, 2021, 9:06 a.m.