As a first approximation
suppressPackageStartupMessages({
library(dplyr)
})
all_comments <- c("I","am","a","trustworthy","person") %>% tolower()
syns <- c("trustworthy","trust-worthy","trusty","confident","confidence","honest","honesty","reliable","reliability","safe","safety","secure","security","assured","care","careful","dependable","sure","integrity","genuine","professional","profesional","proffessional","untrusting","untrustworthy","untrust-worthy","untrusty","unconfident","unconfidence","unhonest","unhonesty","unreliable","unreliability","unsafe","unsafety","unsecure","unsecurity","unassured","uncare","uncareful","undependable","unsure","unintegrity","ungenuine","unprofessional","unprofesional","unproffessional","unproffesional","distrust","distrusting","distrustworthy","distrust-worthy","distrusty","disconfident","disconfidence","dishonest","dishonesty","disreliable","disreliability","dissafe","dissafety","dissecure","dissecurity","disassured","discare","discareful","disdependable","dissure","disintegrity","disgenuine","disprofessional","disprofesional","disproffessional","disproffesional")
all_comments[which(all_comments %in% syns)]
#> [1] "trustworthy"
Then move on to an NLP approach