NBA Stadiums

NBA Stadium Sentiment Examination

Here I have examined review data on NBA stadiums from the website https://www.stadiumjourney.com/stadiums/stadium-journey-s-2023-ranking-of-the-nba-arenas. This data was scraped, but I will provide a copy of the CSV here, but be warned the link will stop working in 89 days.

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.0
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

info_df <- read_csv("https://myxavier-my.sharepoint.com/:x:/g/personal/lewarnd_xavier_edu/EULHOCOPatVIlFuIWeKg7G4BT2hkG8NZ0NuM0N5YGG9Cpw?download=1")

Rows: 1597 Columns: 2
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): stadium_review, name

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Pre-Analysis Context

There is a fair amount of coding that will be run behind the scenes on these visuals, so while the steps of the process will be displayed, the code will not. I will mention which lexicon I used for each question, as I told one of the lexicons I would cite them and I am a man of honor. I also must note that for some reason during my analysis the Sacramento Kings information just disappeared. I have no clue what happened to it, and to all my readers in Sacramento I have no ill will towards the Beam Team.

Analysis

Question 1: What is the overall NCR breakdown of NBA stadiums?

I will answer this by tokenizing my data down to a word level, then I will join in the NRC lexicon, then proceed to graph the total percentage of scoreable words by each of the listed emotions.


Attaching package: 'rvest'

The following object is masked from 'package:readr':

    guess_encoding

Joining with `by = join_by(word)`

This shows that the majority of scoreable words are in the positive and trust categories. This makes sense to me as stadiums are visited most often by fans of that home team, who generally have a positive view of the atmosphere and stadium, which also can help explain anticipation being high as well.

Question 2: Which Los Angles team scores higher?

Currently, both the Los Angles Lakers and the Los Angles Clippers play in the Crypto.com Arena, formerly known as the Staples Center. With the stadiums being the same, I am interested in seeing how the teams reviews rank comparatively. I once again will use the NRC lexicon, and by having the tokenized data from above still keep the words attached to the stadium they were reviewing it is just a matter of filtering down to the desired teams.

The Lakers lead in the positive and trust categories with a large lead over the Clippers in trust. While the Chippers have a slight lead in joy, they also have more frequent appearances of negative, sadness, and anger terms. This could potentially explained by the Lakers having experienced greater team success in the city.

Question 3: What is the general sentiment of every stadium?

In order to get a general overview of positive vs negative I will use the Bing lexicon for this analysis. This will be in in a similar way to the NRC process of joining the lexicon to the terms while keeping it attached to the stadium.

`summarise()` has grouped output by 'name'. You can override using the
`.groups` argument.

Given that Madison Square Garden is often referred to as “The World’s Most Famous Arena” it should come as no surprise it has the highest positive score. Its same city neighbor of the Brooklyn Nets do not fare so well, being the only negatively ranked stadium. This could be due to the design or the arena itself where many have criticized the lack of flair and how steep the seats are, or due to the fact the Nets moved to Brooklyn from New Jersey in the year 2012 and have less local fans or fans who miss getting to go to the old stadium (The IZOD Center).