Social Media Data Analytics from Coursera

Learner Outcomes: After taking this course, you will be able to:

- Utilize various Application Programming Interface (API) services to collect data from different social media sources such as YouTube, Twitter, and Flickr.

- Process the collected data - primarily structured - using methods involving correlation, regression, and classification to derive insights about the sources and people who generated that data.

- Analyze unstructured data - primarily textual comments - for sentiments expressed in them.

- Use different tools for collecting, analyzing, and exploring social media data for research and development purposes.

Sample Learner Story: Data analyst wanting to leverage social media data.

Isabella is a Data Analyst working as a consultant for a multinational corporation. She has experience working with Web analysis tools as well as marketing data. She wants to now expand into social media arena, trying to leverage the vast amounts of data available through various social media channels. Specifically, she wants to see how their clients, partners, and competitors view their products/services and talk about them. She hopes to build a new workflow of data analytics that incorporates traditional data processing using Web and marketing tools, as well as newer methods of using social media data.

Sample Job Roles requiring these skills:

- Social Media Analyst

- Web Analyst

- Data Analyst

- Marketing and Public Relations

Final Project Deliverable/ Artifact: The course will have a series of small assignments or mini-projects that involve data collection, analysis, and presentation involving various social media sources using the techniques learned in the class.

The course was developed by Dr. Chirag Shah while he was a faculty member at Rutgers University. He is currently a faculty member at University of Washington.

What's inside

Syllabus

Introduction to Data Analytics

In this first unit of the course, several concepts related to social media data and data analytics are introduced. We start by first discussing two kinds of data - structured and unstructured. Then look at how structured data, the primary focus of this course, is analyzed and what one could gain by doing such analysis. Finally, we briefly cover some of the visualizations for exploring and presenting data.Make sure to go through the material for this unit in the sequence it's provided. First, watch the four short videos, then take the practice test, followed by the two quizzes. Finally, read the documents about installation and configuration of Python and R. This is very important - before proceeding to the next units, make sure you have installed necessary tools, and also learned how to install new packages/libraries for them. The course expects students to have programming experience in Python and R.

Collecting and Extracting Social Media Data

In this unit we will see how to collect data from Twitter and YouTube. The unit will start with an introduction to Python programming. Then we will use a Python script, with a little editing, to extract data from Twitter. A similar exercise will then be done with YouTube. In both the cases, we will also see how to create developer accounts and what information to obtain to use the data collection APIs. Once again, make sure to go item-by-item in the order provided. Before beginning this unit, ensure that you have all the right tools (Python, R, Anaconda) ready and configured. The lessons depend on them and also your ability to install required packages.

Data Analysis, Visualization, and Exploration

In this unit, we will focus on analyzing and visualizing the data from various social media services. We will first use the data collected before from YouTube to do various statistics analyses such as correlation and regression. We will then introduce R - a platform for doing statistical analysis. Using R, then we will analyze a much larger dataset obtained from Yelp. Make sure you have covered the material in the previous units before proceeding with this. That means, having all the tools (Anaconda, Python, and R) as well as various packages installed. We will also need new packages this time, so make sure you know how to install them to your Python or R. If needed, please review some basic concepts in statistics - specifically, correlation and regression - before or during working on this unit.

Case Studies

In the final unit of this course, we will work on two case studies - both using Twitter and focusing on unstructured data (in this case, text). The first case study will involve doing sentiment analysis with Python. The second case study will take us through basic text mining application using R. We wrap up the unit with a conclusion of what we did in this course and where to go next for further learning and exploration.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines social media data, including structured and unstructured data, for research and development purposes

Taught by Chirag Shah, a recognized expert in social media data analytics

Provides hands-on labs and interactive materials for practical learning

Requires extensive programming experience in Python and R, which may be a barrier for some learners

Involves working with large datasets, which may require specialized software and hardware

Focuses primarily on structured data, which may limit its applicability in certain research areas

Reviews summary

Social media data analytics course

Learners say Social Media Data Analytics is a great course that provides a nice introduction to the field of social media data analysis. The course is informative, well-structured, and engaging. Instructors are knowledgeable and explain concepts clearly. However, some learners have expressed concerns about the course being outdated and having broken links.

Instructors are knowledgeable and explain concepts clearly.

"The course is a great for a start in the social media data analytics. The teacher explains the content very well."

"Instructor was great, deliver lectures really nice."

Course assignments are engaging.

"Give me the way to tackle data collection and analysis with Twitter, YouTube, and Yelp."

"The knowledge is great."

Course provides a good introduction to social media data analysis.

"a nice, easy intro to how to work with APIs, the sample code is a great start to explore further"

"The course is a great for a start in the social media data analytics."

"Overall its a good course but a very basic one."

Some links in the course may be broken.

"Unfrtunately there was a lot of links and codes that weren't working as well as codes and links from few years ago. This course feeds some updates."

"expired links and a file with R code that did not compile."

Course material may be outdated.

"Very outdated. The Twitter API doesn't even work anymore."

"Its informative but certain parts are outdated such as Twitter API and one Python code script other than that its a decent course. "

"The first week was really promising - but rapidly declines in the second week. The course has not been updated since Elon Musk's acquisition of Twitter, which makes some of the work tasks required very hard to complete - unless you have $100 to spare."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Social Media Data Analytics with these activities:

Review Python Syntax

Show steps

Reviewing syntax can activate your memory of key concepts.

Browse courses on Python

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Pick a resource for review
Go through the resource
Try out some simple exercises

Organize Course Materials

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Organizing your materials can help you locate and review them more easily.

Show steps

Create a system for organizing
Go through your materials and organize them
Review your organized materials

Work with Regression Concepts

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Regression analysis is an important technique used in data analysis, so getting extra practice can help you master this technique.

Browse courses on Regression

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Find a dataset
Prepare and clean the data
Run a simple regression model

Three other activities

Expand to see all activities and additional details

Show all six activities

Explore YouTube API

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Gaining more hands-on experience can help you implement API technology more effectively.

Browse courses on Application Programming Interface

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Look for learning resources on the YouTube API
Follow a hands-on tutorial
Apply what you've learned to a personal project

Develop a Content Analysis Project

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Starting a project that incorporates both structured and unstructured data analysis can help you integrate and apply the concepts learned in this course.

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Identify a research question
Collect data from relevant sources
Analyze the data using appropriate methods
Interpret the results and draw conclusions

Join Data Analytics Competition

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Participating in competitions will challenge you to apply your skills in a competitive setting, which can contribute to advancing your knowledge.

Show steps

Identify relevant competitions
Prepare for the competition
Participate in the competition
Reflect on the experience and learnings

Career center

Learners who complete Social Media Data Analytics will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts apply mathematical and statistical techniques to extract meaningful insights from data. They use their findings to help businesses make informed decisions. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Data Analysts who want to work with large and complex datasets.

See salaries and explore the career path for Data Analyst

Social Media Analyst

Social Media Analysts use social media data to understand customer behavior and trends. They use this information to develop and implement social media marketing campaigns. This course provides the skills and knowledge needed to collect, analyze, and interpret social media data. It also covers the use of social media data for research and development purposes, which is a valuable skill for Social Media Analysts who want to stay ahead of the curve.

See salaries and explore the career path for Social Media Analyst

Web Analyst

Web Analysts use data to understand how users interact with websites. They use this information to improve the user experience and increase website traffic. This course provides the skills and knowledge needed to collect, analyze, and interpret web data. It also covers the use of social media data for research and development purposes, which is a valuable skill for Web Analysts who want to gain a deeper understanding of user behavior.

See salaries and explore the career path for Web Analyst

Business Analyst

Business Analysts use data to identify and solve business problems. They use their findings to help businesses make informed decisions. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Business Analysts who want to work with large and complex datasets.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers use data to understand consumer behavior and trends. They use this information to develop and implement marketing campaigns. This course provides the skills and knowledge needed to collect, analyze, and interpret market data. It also covers the use of social media data for research and development purposes, which is a valuable skill for Market Researchers who want to stay ahead of the competition.

See salaries and explore the career path for Market Researcher

Data Scientist

Data Scientists use data to solve complex problems. They use their skills in mathematics, statistics, and computer science to develop and implement data-driven solutions. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Data Scientists who want to work with large and complex datasets.

See salaries and explore the career path for Data Scientist

Actuary

Actuaries use data to assess risk and uncertainty. They use their skills in mathematics, statistics, and finance to create and implement risk management strategies. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Actuaries who want to develop data-driven strategies.

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Customer Success Manager

Customer Success Managers are responsible for ensuring the satisfaction of customers. They use their skills in customer service, sales, and marketing to create and implement customer success strategies. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Customer Success Managers who want to develop data-driven strategies.

See salaries and explore the career path for Customer Success Manager

Public relations manager

Public Relations Managers are responsible for managing the public image of an organization. They use their skills in communications, media relations, and event planning to create and implement public relations campaigns. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Public Relations Managers who want to develop data-driven campaigns.

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Product Manager

Product Managers are responsible for the development and launch of new products. They use their skills in marketing, engineering, and design to create products that meet the needs of customers. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Product Managers who want to develop data-driven products.

See salaries and explore the career path for Product Manager

Sales Manager

Sales Managers are responsible for the development and implementation of sales strategies. They use their skills in sales, marketing, and customer service to create and implement sales strategies that reach and engage customers. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Sales Managers who want to develop data-driven sales strategies.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use their skills in computer science to create software that meets the needs of users. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Software Engineers who want to develop data-driven applications.

See salaries and explore the career path for Software Engineer

Financial Analyst

Financial Analysts use data to analyze the financial performance of companies. They use their skills in finance, accounting, and economics to create and implement financial strategies. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Financial Analysts who want to develop data-driven strategies.

See salaries and explore the career path for Financial Analyst

Marketing Manager

Marketing Managers are responsible for the development and implementation of marketing campaigns. They use their skills in marketing, advertising, and public relations to create campaigns that reach and engage customers. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Marketing Managers who want to develop data-driven campaigns.

See salaries and explore the career path for Marketing Manager

Operations Manager

Operations Managers are responsible for the day-to-day operations of an organization. They use their skills in management, finance, and human resources to create and implement operational strategies. This course provides a strong foundation in data analysis techniques, including data collection, processing, and visualization. It also covers the use of social media data for research and development purposes, which is a valuable skill for Operations Managers who want to develop data-driven strategies.

See salaries and explore the career path for Operations Manager