Data Science
Sentiment Analysis of Twitter using NL toolkit in Python
Make internet a safe place - one hate-free Tweet at a time, and also build an exceedingly impressive proof of work in the field of social media analytics.
Certified by
Role
Data Scientist
Industry
Technology
Menterns at work
35
Level
Advanced
Time Commitment
Submit First Draft in 30 days
Duration
60 days
Tools you’ll learn
Here’s What You Work On
About the Company
Pepper Content brings together the intelligence of humans and machines to create exemplary content for the global market. If you are a writer, Pepper Content has a paid gig for you! And, if you are a company, Pepper can connect you with the best writing talent in the world. Peppertype ai is a product of the company that allows writers to harness the power of AI to generate quick content! Pepper Content is committed to disrupting the world of content creation, and in the process make the internet a kinder, nicer place for companies and humans alike.
Explore
the following work techniques
Python
NLTK
Sentiment Analysis
SVM (Support Vector Machines)
Logistic Regression
Learn more about our Menternship Principle
Bridging the gap
6000 people take to Twitter every minute to express an opinion, or share a piece of information. A number of these tweets can be problematic, because they would incite hate and prejudice against a section of the society, or worse - spread false information about critical global issues like the Coronavirus pandemic. It is the task of a data science team at Twitter to create product policies which enable Twitter algorithms to flag and mark problematic tweets - making the platform safer for its user. In this menternship, you will be tasked with creating your own version of a sentiment analysis algorithm that can regulate problematic content on a social media platform.
Apply
the following skills
Data Analysis
Data preparation
Hypothesis testing
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Expected output
In this menternship, you will develop a sentiment analysis algorithm to identify and flag problematic Tweets on Twitter
Create
the following deliverables
Data preparation of the given dataset
A Twitter sentiment analysis model that identifies the sentiments of the tweets using various ML Algorithms
Learn more about our Menternship Principle
What you’ll need before starting
Python, Sentiment Analysis
Why Do Menternships?
Each Menternship experience is powered by the MentorMind experiential learning model. We empower you as a Mentern to produce your own unique real work output through mentoring, deep-learning & applying your learnings to work.
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You get access to a guild of industry mentors with remarkably diverse experience in their fields. Mentors help you with expert advice, domain guidance or to understand a specific task better. Moreover, you can always depend on our community of menterns, MentorMind Garage, to seek assistance from your co-menterns, guides & mentors!
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Meet Our Certified Menterns
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Sentiment Analysis of Twitter using NL toolkit in Python
Make internet a safe place - one hate-free Tweet at a time, and also build an exceedingly impressive proof of work in the field of social media analytics.
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Get Guidance in One-on-One Mentor Hours
Ask Questions in our Biweekly AMA
Resolve all doubts on Mentor Support Chatbox
Get Actionable Mentor Feedback on your work
Learn & Network at the exclusive Mentern Perks Club
