Cluster 1
pal <- brewer.pal(8,"Dark2")
cluster_1 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
Cluster 2
cluster_2 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL2") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
Cluster 3
cluster_3 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL3") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): mangroves could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): implications could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): services could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): assessment could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): planning could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): effects could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): florida could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): forests could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): natural could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): spatial could not be fit on page. It will not be plotted.
Cluster 4
cluster_4 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL4") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 5
cluster_5 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL5") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 6
cluster_6 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL6") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 7
cluster_7 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL7") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): engineering could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): geomorphology could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): development could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): sensing could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): planning could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): evolution could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): portugal could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): processes could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): mediterranean could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): modelling could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): natural could not be fit on page. It will not be plotted.
Cluster 8
cluster_8 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL8") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 9
cluster_9 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL9") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 10
cluster_10 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL10") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 11
cluster_11 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL11") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 12
cluster_12 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL12") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 13
cluster_13 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL13") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 14
cluster_14 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL14") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 15
cluster_15 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL15") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 16
cluster_16 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL16") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 17
cluster_17 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL17") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): development could not be fit on page. It will not be plotted.
Cluster 18
cluster_18 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL18") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 19
cluster_19 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL19") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 20
cluster_20 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL20") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): environment could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): monitoring could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): research could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): structure could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): biological could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): breeding could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): indicators could not be fit on page. It will not be plotted.
Cluster 21
cluster_21 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL21") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 22
cluster_22 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL22") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 23
cluster_23 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL23") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 24
cluster_24 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL24") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 25
cluster_25 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL25") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
Cluster 26
cluster_26 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL26") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): groundwater could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): harmonizing could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): hydrogeol could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): hydrogeological could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): hydrological could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): hydrologiques could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): region could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): schultz could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): social could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): stressed could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): technology could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): tolmach could not be fit on page. It will not be plotted.
## Warning in wordcloud(word, n, random.order = FALSE, max.words = 50, colors =
## pal): urban could not be fit on page. It will not be plotted.
Cluster 27
cluster_27 <-
read_excel("~/Library/CloudStorage/GoogleDrive-sebastian.robledogi@amigo.edu.co/My Drive/A. RESEARCH/Papers Luis Amigo/Botero et al 2022/data/coastal_man(19may).xlsx", sheet = "CL27") |>
unnest_tokens(output = word,
input = full_name) |>
dplyr::anti_join(stop_words) |>
count(word, sort = TRUE) |>
filter(word == str_remove(word, pattern = "coast.*"),
word == str_remove(word, pattern = "manag.*"),
word == str_remove(word, pattern = "pp"),
word == str_remove(word, pattern = "1"),
word == str_remove(word, pattern = "[0-9]"),
word == str_remove(word, pattern = "\\."),
word == str_remove(word, pattern = "ocean"),
word == str_remove(word, pattern = "zone"),
word == str_remove(word, pattern = "integrat.*"),
word == str_remove(word, pattern = "marine"),
word == str_remove(word, pattern = "journal"),
word == str_remove(word, pattern = "http.*"),
word == str_remove(word, pattern = "doi"),
word != str_remove(word, pattern = "[a-z]{4}")) |>
with(wordcloud(word,
n, random.order = FALSE,
max.words = 50,
colors = pal))
## New names:Joining, by = "word"
