edgar (version 2.0.1)

getSentiment: Provides sentiment measures of EDGAR filings

Description

getSentiment computes sentiment measures of EDGAR filings

Usage

getSentiment(cik.no, form.type, filing.year)

Arguments

cik.no

vector of CIK number of firms in integer format. Suppress leading zeroes from CIKs. Keep cik.no = 'ALL' if needs to download for all CIKs.

form.type

character vector containing form type to be downloaded. form.type = 'ALL' if need to download all forms.

filing.year

vector of four digit numeric year

Value

Function returns dataframe containing CIK number, company name, date of filing, accession number, and various sentiment measures. This function takes the help of Loughran-McDonald (L&M) sentiment dictionaries (https://sraf.nd.edu/textual-analysis/resources/) to compute sentiment measures of a EDGAR filing. Following are the definitions of the text characteristics and the sentiment measures:

file.size = Total number of words in the filing. It does not consider stop words.

char.count = Total number of characters in the filing. It does not consider stop words.

complex.word.count = Total number of complex words in filing. A word is count as a complex word if contains vowels(a, e, i, o, u) more than three times. It does not consider stop words.

lm.dictionary.count = The number of words that occur in the L&M master dictionary.

lm.negative.count = The number of L&M Financial-Negative words in the filing.

lm.positive.count = The number of L&M Financial-Positive words in the filing.

lm.strong.modal.count = The number of L&M Financial-Strong Modal words in the filing.

lm.moderate.modal.count = The number of L&M Financial-Moderate Modal words in the filing.

lm.weak.modal.count = The number of L&M Financial-Weak Modal words in the filing.

lm.uncertainty.count = The number of L&M Financial-Uncertainty words in the filing.

lm.litigious.count = The number of L&M Financial-Litigious words in the filing.

harvard.negative.count = Number of words in the filing. that occur in the Harvard General Inquirer Negative word list, as defined by L&M.

Details

getSentiment function takes CIK(s), form type(s), and year(s) as input parameters. The function first imports available downloaded filings in local woking directory 'Edgar filings' created by getFilings function; otherwise, it downloads the filings which is not already been downloaded. It then reads the filings, cleans the filings, and computes the sentiment measures. The function returns a dataframe with filing information, and sentiment measures.

Examples

# NOT RUN {
senti.df <- getSentiment(cik.no = c('1000180', '38079'), 
                         form.type = '10-K', filing.year = 2006) 
                         
## Returns dataframe with sentiment measures of firms with CIKs 
1000180 and 38079 filed in year 2006 for form type '10-K'.

senti.df <- getSentiment(cik.no = '38079', form.type = c('10-K', '10-Q'), 
                         filing.year = c(2005, 2006))
# }