conference_call_segmenter {disclosuR}

Earnings call segmenter

Description

Converts one earnings call transcript from 'FairDisclosure' obtained from 'NexisUni' to an R data frame.

Usage

conference_call_segmenter(
  file,
  sentiment = FALSE,
  emotion = FALSE,
  regulatory_focus = FALSE,
  laughter = FALSE,
  narcissism = FALSE
)

Arguments

file

The name of the PDF file which the data are to be read from. If it does not contain an absolute path, the file name is relative to the current working directory, getwd().

sentiment

Performs dictionary-based sentiment analysis based on the analyzeSentiment function (default: FALSE)

emotion

Performs dictionary-based emotion analysis based on the get_nrc_sentiment function (default: FALSE)

regulatory_focus

Calculates the number of words indicative for promotion and prevention focus based on the dictionary developed by Gamache et al., 2015 (default: FALSE)

laughter

Counts the number of times laughter was indicated in a quote. (default: FALSE)

narcissism

Counts the number of pronoun usage and calculates the ratio of first-person singular to first-person plural pronouns. This measure is derived from Zhu & Chen, (2015 (default: FALSE)

Value

An R data frame with each row representing one quote. The columns indicate the quarter, year, section (presentation versus Q&A), the speaker's name, role, affiliation, and also three binary indicators on whether the speaker is the host company's (1) CEO, (2) CFO, and/or (3) Chairman.

Examples

earnings_calls_df <- conference_call_segmenter(file = system.file("inst",
"examples",
"earnings_calls", "earnings_example_01.pdf",
package = "disclosuR"));
earnings_calls_df_sentiment <- conference_call_segmenter(file = system.file("inst",
"examples",
"newswire", "earnings_example_01.pdf",
package = "disclosuR"),
sentiment = TRUE);