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

No. of Subscribers

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

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

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

What you’ll need before starting

Python, Sentiment Analysis