Calculate the Transient Impression after an Event

transient_impression(
  d,
  equation_key = NULL,
  equation_gender = NULL,
  eq_df = NULL,
  ...
)

Arguments

d: data that has been reshaped to be in long format, with columns: element, term, component, event, event_id, dimension, and estimate
equation_key: the actdata equation key for the equation to use to get the transient impression
equation_gender: male, female, or average, corresponding to the gender of equation to use when calculating the transient impression
eq_df: use this only if you have used your own equation and not one in actdata

Value

dataframe in long format, with one row for each element-dimension of the event, columns for fundamental sentiment and transient impression.

Examples

d <- tibble::tibble(actor_modifier = "tired", actor = "ceo", behavior = "advise", object = "benefactor")
d <- reshape_events_df(df = d, df_format = "wide", dictionary_key = "usfullsurveyor2015", dictionary_gender = "average")
#> Joining, by = c("term", "component")
transient_impression(d = d, equation_key = "us2010", equation_gender = "average")
#>    element       term component dimension estimate  trans_imp
#> 1    actor  tired ceo  identity         E -0.79846  0.9841138
#> 2    actor  tired ceo  identity         P  1.21070  0.9023990
#> 3    actor  tired ceo  identity         A -0.48800 -0.1250800
#> 4 behavior     advise  behavior         E  2.57000  1.0171968
#> 5 behavior     advise  behavior         P  2.28000  1.6511710
#> 6 behavior     advise  behavior         A  0.28000  0.0922000
#> 7   object benefactor  identity         E  1.97000  1.8357522
#> 8   object benefactor  identity         P  1.98000  0.9686181
#> 9   object benefactor  identity         A  0.10000 -1.1940028