I love to read and compose poetry and this poem is one that I wrote for my grade 7 Language Arts class. Thus, I was pleasantly suprised when I came across Yihui’s blog because I never knew that I could integrate my passion for poetry with my passion for R. Thank you so much Yihui; I appreciate it. What I’d like to attempt is a sentiment analysis using Julia Stilge’s Text Mining with r so I can see the general feeling my poem gives out.
What We Take For Granted
My fellow gentlemen, take some advice from me
As I wander around eternally
Thinking of how I paid the ultimate cost
A silent spectator to all I have lost
Let me start at the beginning in New York city
Where I met a young lady, clever and pretty
We had dinner and drinks at Le Bernardin
And danced until dawn at the downtown scene
A week later she informed me “I’m studying for the bar”
And laughed as I almost tripped into a car
“It’s not very feminine”, my words left hanging
“This is 1964” she frowned, “the world is changing”
Months later I proposed and we moved in together
In a luxury penthouse just off 21’st and Heather
She bought a hi fi phono and let it blast
100 little records of rock, rhythm and jazz
On the weekdays I worked my 9 to 5
Managing numbers for the Wall Street jive
And every night I came home to our dinner table
And we ate her roasted chicken with sugar maple
Oh, didn’t it seem as though I had I all?
Wealthy and charming at functions and balls
With a beautiful fiance, never dull never aged
When she found employment, all of that changed
Now, I was not a misogynistic man
Nor did I want her dressed in gloves and fans
But we all have a place, come destiny or doom
And a young woman’s place is not in a courtroom
You should have heard the screaming and the yelling
She was deaf to all reason, deaf to my tellings
Deaf to my warnings and deaf to my pleading
I only ever kept a lookout for her well being
That evening I was in a terrible rage
Drove like a madman, revved the pedal gage
So to the loads traffic I paid no attention
Not seeing the cars coming from all directions
When we collided it was as if time had froze
Then back came reality, in three sharp blows
The sirens, the commotion, a crescendo of screams
The smell of blood mingling with petrol gasoline
For as long as I could remember, I had always feared dying
But I felt no fear, not at all terrifying
The emotion that filled me was bitter regret
Of all of the things that her and I had said
Mourning for the life I could have lived
For I could take and take but never give
Regret for not appreciating, opposed to being glad
Regret for the best thing that I never had
Now for my sentiment analysis on a set of my poems that I have saved as a pdf file. Let’s load the required libraries.
library(tidyverse)
library(pdftools)
library(tidytext)
library(wordcloud)
library(reshape2)Now I will load my poems from the pdf file
tara_poems<-pdf_text("../../static/data/Poems_TK.pdf")
table_tara_poem <- data.frame(text = unlist(strsplit(tara_poems, "\n"))) %>%
mutate(poem = "all_my_poems", line = row_number(), text = gsub("\n", "", text))
#head(table_tara_poem)
tara_poem_text<- table_tara_poem %>%
as_tibble() %>%
unnest_tokens(word, text) %>%
anti_join(stop_words)## Joining, by = "word"tara_poem_text## # A tibble: 347 × 3
## poem line word
## <chr> <int> <chr>
## 1 all_my_poems 100 scythe
## 2 all_my_poems 100 bullet
## 3 all_my_poems 100 exempt
## 4 all_my_poems 99 subdue
## 5 all_my_poems 99 cruel
## 6 all_my_poems 98 ornament
## 7 all_my_poems 97 someplace
## 8 all_my_poems 96 fortunate
## 9 all_my_poems 95 cocoon
## 10 all_my_poems 95 guarded
## # ... with 337 more rowstara_poem_text %>%
inner_join(get_sentiments("bing")) %>%
count(word, sentiment, sort = TRUE) %>%
acast(word~sentiment, value.var = "n", fill = 0) %>%
comparison.cloud(colors = c("gray20", "gray80"), max.words = 100)
Appears my poems reflect quite a bit of negative sentiment. Next, I’ll try and evaluate my essays @language Arts class.