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.

Traffic lights

Read about what's good

what should give you pause

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

Practical social media data analysis overview

According to learners, this course offers a strong foundation and a good overview of social media data analysis, effectively demonstrating the use of Python and R. A significant strength highlighted by many is the focus on practical application through hands-on projects and labs that use real-world datasets, which students found highly valuable and directly applicable. However, a frequent point of criticism, noted across recent reviews, is that the course content, particularly related to API access (like the Twitter API), is outdated and may not work as described, creating significant hurdles. Additionally, some students reported frustrating technical setup issues with software and packages, suggesting the course assumes a higher level of programming expertise than just "basic" and could benefit from updated instructions.

Provides a solid foundation but can feel rushed.

"It's a solid foundation, but don't expect to become an expert solely from this."

"some parts felt a bit rushed, and the examples could have been more in-depth..."

"Provides a solid foundation."

Assumes more programming skill than "basic".

"...assumed more prior knowledge than I expected, even with basic programming experience."

"Assumes a very high level of prior technical expertise, more than 'basic programming'."

"Good course if you already have strong programming skills."

"Requires dedication and some programming background."

Instructor explains concepts clearly.

"...the instructor's explanations were clear."

"Instructor explains concepts clearly."

Hands-on projects and labs use real data.

"the project was awesome and got me to try real-world datasets and see the challenges on data cleaning..."

"The labs were practical and the instructor's explanations were clear."

"Provides a hands-on approach to analyzing social media data. The projects are very practical..."

"The practical exercises using real data were very helpful."

"The projects are challenging and force you to apply what you learned."

"The hands-on parts were the most valuable."

Installation and dependency setup can be frustrating.

"the technical setup instructions were confusing and outdated. Spent a lot of time troubleshooting Python and R installations..."

"The technical hurdles were immense, and the support was not helpful."

"However, the technical setup was frustrating..."

API information, especially Twitter, is outdated.

"My main criticism is that the course could benefit from updated materials, particularly the parts dealing with API access..."

"Very disappointed. The course material, especially regarding the APIs, is outdated and does not work as described."

"The Python API sections were a bit tricky due to changes in the platforms (Twitter API specifically)."

"...some API methods shown don't work anymore. Needs significant updates to be truly practical in 2023."

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

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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.

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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

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

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

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

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.

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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

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

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.

See salaries and explore the career path for Public relations 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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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.

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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.

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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.

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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.

See salaries and explore the career path for Actuary