Playing Around with the Prismatic Topic Graph API using R
The Prismatic Team has slowly been rolling out a very cool API. You can read all about it here. At the same time, I have been using this as an opportunity to learn how to create an R package.
After today’s API update to identify the relevant content related to a specific topic, I wanted to highlight what is possible with a few lines of code using the prismaticR package. Needless to say, my package is raw, but I wanted to demonstrate some of the cool things that you can do.
Let’s get started
First things first, you can use devtools to install the prismaticR package.
## install devtools package -- uncomment line below if you need to install
# install.packages("devtools")
library(devtools)
## install my prismaticR package if you havent already
install_github("btibert3/prismaticR")
## now lets load it
library(prismaticR)
Before you move forward, you will need to get an API token for your calls. You can get that token here.
Store your token in an object called TOKEN …
TOKEN = "YOUR_TOKEN_HERE"
Explore the API
The first thing that we should do is crawl the topic id database. We will use this later …
tids = prizTID()
# ## keep everything lower case
tids$topic = tolower(tids$topic)
We can use the stringr package to filter topic names based on keywords of interest. For example, how many of the topics include the term admission
tids[str_detect(tids$topic, "admission"),]
id topic
993 993 college admissions
A broader keyword …
tids[str_detect(tids$topic, "higher ed"),]
id topic
1929 1929 higher education
How about college?
head(tids[str_detect(tids$topic, "college"),], 10)
id topic
182 182 amherst college
433 433 bard college
434 434 barnard college
447 447 baruch college
592 592 boston college
593 593 boston college eagles football
605 605 bowdoin college
659 659 brooklyn college
993 993 college admissions
994 994 college athletics
And university? ..
head(tids[str_detect(tids$topic, "university"),], 10)
id topic
34 34 adelphi university
243 243 appalachian state university
278 278 arizona state university
348 348 auburn university
468 468 baylor university
565 565 bob jones university
636 636 brigham young university
732 732 california state university
786 786 carnegie mellon university
1558 1558 florida state university
And to close it out, how about student …
tids[str_detect(tids$topic, "student"),]
id topic
1591 1591 foreign students
1746 1746 gifted students
1780 1780 graduate schools and students
4249 4249 student loans
This might be a good time to use the similar topic API. To keep it simple, let’s identify the topics that are related to the topic of Harvard University …
harvard = tids[str_detect(tids$topic, "harvard uni"),]$id
prizSIM(TOKEN, TID = harvard)
topic_id topic score
1 1139 Dallas Mavericks 0.28756
Interesting. How about Amherst College? …
prizSIM(TOKEN, TID = 182)
topic_id topic score
1 4866 Williams College 0.32472
The API even allows to identify the current stories relevant to college admissions? The top 5 are …
score url
1 0.66227 http://now.dartmouth.edu/2015/03/2120-students-offered-acceptance-into-the-class-of-2019/
2 0.64772 http://college.usatoday.com/2015/03/31/i-didnt-get-into-my-first-choice-college-now-what/
3 0.62981 http://dailyprincetonian.com/news/2015/03/admissions/
4 0.62837 http://www.nj.com/mercer/index.ssf/2015/03/princeton_university_has_most_selective_admissions.html
5 0.62516 http://www.nj.com/essex/index.ssf/2015/03/newark_students_get_on-the-spot_college_acceptance.html
And for the sake of bots, here is the title of the “hottest” page above …
x_resp = html(x$url[1])
html_node(x_resp, "title") %>% html_text()
[1] "2,120 Students Offered Acceptance Into the Class of 2019 | Dartmouth Now"
Summary
Have fun. I make no warantees for the R package, but with a few calls, you can do some really cool things.
