NYC Data Science Academy| Blog
Bootcamps
Lifetime Job Support Available Financing Available
Bootcamps
Data Science with Machine Learning Flagship ๐Ÿ† Data Analytics Bootcamp Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lesson
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories Testimonials Alumni Directory Alumni Exclusive Study Program
Courses
View Bundled Courses
Financing Available
Bootcamp Prep Popular ๐Ÿ”ฅ Data Science Mastery Data Science Launchpad with Python View AI Courses Generative AI for Everyone New ๐ŸŽ‰ Generative AI for Finance New ๐ŸŽ‰ Generative AI for Marketing New ๐ŸŽ‰
Bundle Up
Learn More and Save More
Combination of data science courses.
View Data Science Courses
Beginner
Introductory Python
Intermediate
Data Science Python: Data Analysis and Visualization Popular ๐Ÿ”ฅ Data Science R: Data Analysis and Visualization
Advanced
Data Science Python: Machine Learning Popular ๐Ÿ”ฅ Data Science R: Machine Learning Designing and Implementing Production MLOps New ๐ŸŽ‰ Natural Language Processing for Production (NLP) New ๐ŸŽ‰
Find Inspiration
Get Course Recommendation Must Try ๐Ÿ’Ž An Ultimate Guide to Become a Data Scientist
For Companies
For Companies
Corporate Offerings Hiring Partners Candidate Portfolio Hire Our Graduates
Students Work
Students Work
All Posts Capstone Data Visualization Machine Learning Python Projects R Projects
Tutorials
About
About
About Us Accreditation Contact Us Join Us FAQ Webinars Subscription An Ultimate Guide to
Become a Data Scientist
    Login
NYC Data Science Acedemy
Bootcamps
Courses
Students Work
About
Bootcamps
Bootcamps
Data Science with Machine Learning Flagship
Data Analytics Bootcamp
Artificial Intelligence Bootcamp New Release ๐ŸŽ‰
Free Lessons
Intro to Data Science New Release ๐ŸŽ‰
Find Inspiration
Find Alumni with Similar Background
Job Outlook
Occupational Outlook
Graduate Outcomes Must See ๐Ÿ”ฅ
Alumni
Success Stories
Testimonials
Alumni Directory
Alumni Exclusive Study Program
Courses
Bundles
financing available
View All Bundles
Bootcamp Prep
Data Science Mastery
Data Science Launchpad with Python NEW!
View AI Courses
Generative AI for Everyone
Generative AI for Finance
Generative AI for Marketing
View Data Science Courses
View All Professional Development Courses
Beginner
Introductory Python
Intermediate
Python: Data Analysis and Visualization
R: Data Analysis and Visualization
Advanced
Python: Machine Learning
R: Machine Learning
Designing and Implementing Production MLOps
Natural Language Processing for Production (NLP)
For Companies
Corporate Offerings
Hiring Partners
Candidate Portfolio
Hire Our Graduates
Students Work
All Posts
Capstone
Data Visualization
Machine Learning
Python Projects
R Projects
About
Accreditation
About Us
Contact Us
Join Us
FAQ
Webinars
Subscription
An Ultimate Guide to Become a Data Scientist
Tutorials
Data Analytics
  • Learn Pandas
  • Learn NumPy
  • Learn SciPy
  • Learn Matplotlib
Machine Learning
  • Boosting
  • Random Forest
  • Linear Regression
  • Decision Tree
  • PCA
Interview by Companies
  • JPMC
  • Google
  • Facebook
Artificial Intelligence
  • Learn Generative AI
  • Learn ChatGPT-3.5
  • Learn ChatGPT-4
  • Learn Google Bard
Coding
  • Learn Python
  • Learn SQL
  • Learn MySQL
  • Learn NoSQL
  • Learn PySpark
  • Learn PyTorch
Interview Questions
  • Python Hard
  • R Easy
  • R Hard
  • SQL Easy
  • SQL Hard
  • Python Easy
Data Science Blog > Data Visualization > Twitter Scraping

Twitter Scraping

Denis Nguyen
Posted on May 28, 2016

Contributed by Denis Nguyen. He is currently in the NYC Data Science Academy 12 week full-time Data Science Bootcamp program taking place between April 11th to July 1st, 2016. This post is based on his third class project - Web Scraping (due on the 6th week of the program).

 

Twitter is an online social networking service in which users send short messages called "tweets." Tweets may include media such as pictures, videos, links, making it a very informative source of information. Some people use Twitter as a media outlet and stay up-to-date with current events just by reading Twitter. Others use Twitter to voice their thoughts about events and topics and this has made Twitter a rich source of information for data analytics. By analyzing tweets, one can understand what people may feel about certain events or companies and this becomes valuable actionable information for marketing companies. With the presidential election approaching, I wanted to see what our presidential candidate Donald Trump tweeted the most and how his tweets have changed throughout the campaign.  People have said how his use of Twitter has been an integral part of his campaign and analyzing them would give us more information.

 

The Data

Donald Trump announced his presidential campaign on June 16, 2015 so tweets from @realDonaldTrump were retrieved from June 1, 2015 to May 20, 2016. Tweets contained text, time of post, hashtags, replies, locations, and number of likes and retweets. The information was organized in the table shown below.

twitdata

 

Strategy for Scraping

Twitter provides APIs to help retrieve tweets but because this project was putting what I learned about web scraping to the test, I decided to stick to Python and write my own script to get the data. Upon research, I found out that APIs placed a limit on the amount of information attained but my script does not have this limit. Unfortunately, simply loading the url with Python and retrieving information did not work and would only retrieve 20 tweets. This occurred because Twitter only loads 20 tweets at a time and would load the next 20 when the bottom of the web page was reached. Selenium was used to overcome this obstacle. Selenium opens up the web page in a browser and scrolls down until it reaches the last tweet. Once this is done, it retrieves information and puts it in a table.

Selenium seems to have a limit of 10,000 tweets as the Selenium browser does not look like it can handle all the media in the tweets.

The following code can be adapted to any page.

Analysis

Likes and Retweets

Upon analyzing the number of likes and retweets, Trump's tweets received, we see a large range in numbers. Likes ranged from 14 to 110,000 while retweets ranged from 2 to 85,000. This large range can be seen in the progression of his tweets. Before he announced his candidacy, his tweets only received a couple hundred likes and retweets but is now averaging a couple thousand likes and retweets. His number of posts has also increased over time so whatever Trump is doing must be working in getting him more attention and media coverage.

likes/retweets

Location

Although not all of Trump's tweets have location, it is interesting to see where most of his tweets are coming from. It would make sense that most of his tweets are in the northeast region but other frequent tweet locations occurred in places where he stopped at during his campaign. Some places like United States and Trump Tower are not very specific so it is also questionable how Twitter allows locations to be picked.

locations

Hashtags

Hashstags most frequently used in Trump's tweets are #Trump2016 and #MakeAmericaGreatAgain, which would make sense since those 2 hashtags are his slogan. His top hashtags are political terms/politically related with the exception of #SNL, which is Saturday Night Live. Perhaps Trump has been featured on that show a couple times and therefore he has mentioned them in his tweets.

tags

Replies

One way Trump must be using his Twitter to help him stay on people's minds is by tweeting at media. Most of his replies are to media such as @FoxNews and @CNN, with the exception of @JebBush and @Macys. It would make sense that his political opponent is mentioned but we may look further into Trump's association with Macy's.

hashtags

Word Count

The number of words that Trump uses in his tweets are interesting to analyze. I would think that words pertaining to certain controversial topics would be mentioned but the top words are not negative as people have been saying. After removing "stop words" which are words commonly used in English such as "the" and "is," we have a list of his most frequently used words. Even after removing hashtags and replies in the word count, we see that words from his slogan "Make America Great Again" are in the top list. His name is also used a lot but that may be from quoting articles and tweets about him.

words

Conclusion

Trump has used Twitter as a way to stay on people's minds and in media's spotlight. The number of tweets made over his campaign has increased and the number of likes and retweets has increased. We do not know if this means that he will win the election but it does show us how much of an impact social media platforms such as Twitter can have on a presidential election.

The following are a couple conclusions after analyzing his tweets:

 

  • In about a year, Trump has grown the number of likes and retweets from under 50 to a couple thousand per tweet
  • Most of Trump's tweets with location are from Manhattan and New Jersey
  • Trump's 20 most frequent hashtags are political terms, with the exception of #SNL
  • #Trump2016 and #MakeAmericaGreatAgain are the top two
  • Trump tweets at media the most, with the exception of Jeb Bush who is his 4th favorite Twitter buddy
  • 'Trump" appears the most in the tweets, coming from articles and replies

Future steps are to analyze #AskTrump, which was the questionnaire that Trump announced on Twitter. The number of tweets were over 10,000 and Selenium had problems loading all of them so we will want to collect smaller number of tweets at a time and the combine the information. Doing sentiment analysis and seeing how feelings about Trump have changed over time would also give us an idea of how his campaign is going and may help us predict whether he may win the election.

About Author

Denis Nguyen

With a background in biomedical engineering and health sciences, Denis has a passion for finding patterns and optimizing processes. He developed his interest for data analysis while doing research on the effects of childhood obesity on bone development...
View all posts by Denis Nguyen >

Related Articles

Capstone
Catching Fraud in the Healthcare System
Capstone
The Convenience Factor: How Grocery Stores Impact Property Values
Capstone
Acquisition Due Dilligence Automation for Smaller Firms
Machine Learning
Pandemic Effects on the Ames Housing Market and Lifestyle
Machine Learning
The Ames Data Set: Sales Price Tackled With Diverse Models

Leave a Comment

Cancel reply

You must be logged in to post a comment.

Mark March 18, 2018
Hello Danis, thanks for sharing this script! I would like to ask you how can I put a limit to the "page scroll" (i.e. move down the page for 5 times, 10 times, 10000 times). Tnx! :)
To Tweet or Not to Tweetโ€ฆ โ€“ Ms. Cameron September 26, 2017
[โ€ฆ] Image via Denis Nguyen [โ€ฆ]

View Posts by Categories

All Posts 2399 posts
AI 7 posts
AI Agent 2 posts
AI-based hotel recommendation 1 posts
AIForGood 1 posts
Alumni 60 posts
Animated Maps 1 posts
APIs 41 posts
Artificial Intelligence 2 posts
Artificial Intelligence 2 posts
AWS 13 posts
Banking 1 posts
Big Data 50 posts
Branch Analysis 1 posts
Capstone 206 posts
Career Education 7 posts
CLIP 1 posts
Community 72 posts
Congestion Zone 1 posts
Content Recommendation 1 posts
Cosine SImilarity 1 posts
Data Analysis 5 posts
Data Engineering 1 posts
Data Engineering 3 posts
Data Science 7 posts
Data Science News and Sharing 73 posts
Data Visualization 324 posts
Events 5 posts
Featured 37 posts
Function calling 1 posts
FutureTech 1 posts
Generative AI 5 posts
Hadoop 13 posts
Image Classification 1 posts
Innovation 2 posts
Kmeans Cluster 1 posts
LLM 6 posts
Machine Learning 364 posts
Marketing 1 posts
Meetup 144 posts
MLOPs 1 posts
Model Deployment 1 posts
Nagamas69 1 posts
NLP 1 posts
OpenAI 5 posts
OpenNYC Data 1 posts
pySpark 1 posts
Python 16 posts
Python 458 posts
Python data analysis 4 posts
Python Shiny 2 posts
R 404 posts
R Data Analysis 1 posts
R Shiny 560 posts
R Visualization 445 posts
RAG 1 posts
RoBERTa 1 posts
semantic rearch 2 posts
Spark 17 posts
SQL 1 posts
Streamlit 2 posts
Student Works 1687 posts
Tableau 12 posts
TensorFlow 3 posts
Traffic 1 posts
User Preference Modeling 1 posts
Vector database 2 posts
Web Scraping 483 posts
wukong138 1 posts

Our Recent Popular Posts

AI 4 AI: ChatGPT Unifies My Blog Posts
by Vinod Chugani
Dec 18, 2022
Meet Your Machine Learning Mentors: Kyle Gallatin
by Vivian Zhang
Nov 4, 2020
NICU Admissions and CCHD: Predicting Based on Data Analysis
by Paul Lee, Aron Berke, Bee Kim, Bettina Meier and Ira Villar
Jan 7, 2020

View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day ChatGPT citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay football gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income industry Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI

NYC Data Science Academy

NYC Data Science Academy teaches data science, trains companies and their employees to better profit from data, excels at big data project consulting, and connects trained Data Scientists to our industry.

NYC Data Science Academy is licensed by New York State Education Department.

Get detailed curriculum information about our
amazing bootcamp!

Please enter a valid email address
Sign up completed. Thank you!

Offerings

  • HOME
  • DATA SCIENCE BOOTCAMP
  • ONLINE DATA SCIENCE BOOTCAMP
  • Professional Development Courses
  • CORPORATE OFFERINGS
  • HIRING PARTNERS
  • About

  • About Us
  • Alumni
  • Blog
  • FAQ
  • Contact Us
  • Refund Policy
  • Join Us
  • SOCIAL MEDIA

    ยฉ 2025 NYC Data Science Academy
    All rights reserved. | Site Map
    Privacy Policy | Terms of Service
    Bootcamp Application