Removing Apostrophies while text mining, or don't - r

Question

This is absolutely driving me nuts, and I'm ashamed to say that I've spent the last 3 hours trying to figure this out.
I'm mining tweeter data, and I'd like to do some text analysis, but words like "doesn't" are throwing me off. I either want to keep the ' or replace it with an empty string (""). I've tried:
tweets$text <- gsub("\'", "", tweets$text)
tweets$text <- gsub("\\'", "", tweets$text)
tweets$text <- gsub("'", "", tweets$text)
tweets$text <- gsub("\W", "", tweets$text)
What I WANT is doesn't -> doesnt OR doesn't.
I want to remove the rest of the special characters, but because what comes after ' changes the word, I want to keep that. Later in the code I'm using gsub("[^A-Za-z]", " ", twt_txt_url) to clean the special characters.
I shared this code earlier for a different question, but it should still get the point across. Note that this is split into two codes, one for you to pull the data, and two to see how I'm cleaning.
PULLING DATA:
library(rtweet)
library(tidyverse)
library(httpuv)
# API access keys
app_name = "app_name"
consumer_key <- "consumer_key"
consumer_secret <- "consumer_secret"
access_token <- "access_token"
access_secret <- "access_secret"
# Create twitter connection
create_token(app = app_name,
consumer_key = consumer_key,
consumer_secret = consumer_secret,
access_token = access_token,
access_secret = access_token_secret)
# who do we want to observe
account <- "#BillGates"
# 3200 is the max we can pull at once
account.timeline <- get_timeline(account, n=100, includeRts =TRUE)
# create data frame and csv from tweets
write_as_csv(account.timeline, BillGates.csv", fileEncoding = "UTF-8")
CLEANING DATA
library(tidyverse)
library(qdapRegex)
library(tm)
library(qdap)
library(wordcloud)
tweets <- read_csv("BillGate.csv")
# This is where I'm trying to remove the ' from words
tweets$text <- gsub("\\'","", tweets$text)
# Separate out the text column
twt_txt <- tweets$text
# remove URLs
twt_txt_url <- rm_twitter_url(twt_txt)
# remove special characters
twt_txt_chrs <- gsub("[^A-Za-z]", " ", twt_txt_url)
# convert to a text corpus
twt_corpus <- twt_txt_chrs %>%
VectorSource() %>%
Corpus()
Here's some of the data that you can manipulate as well. It seems like I can remove the first ', but nothing after that.
df = data.frame(
tweet = c(1, 2, 3, 4, 5),
text = c(
"Standing up for science has never been more important. Congratulations to Dr. Anthony Fauci and Dr. Salim Abdool Karim on receiving this honor.",
"I've known and learned from #RonConway for more than 40 years. I'm glad to see #svangel team up with #bchesky to mentor and support companies working to create more economic empowerment opportunities for people across the world.",
"This book has nothing to do with viruses or pandemics. But it is surprisingly relevant for these times. #exlarson provides a brilliant and gripping account of another era of widespread anxiety: the years 1940 and 1941.",
"The season finale of our podcast features two incredible people who are using their positions as artists to change the world for the better.",
"Like many people, I’ve tried to deepen my understanding of systemic racism in recent months. If you’re interested in learning more about the lives caught up in our country's justice system, I highly recommend #thenewjimcrow by Michelle Alexander."
)
)