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Computational Social Science Methods

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Computational Social Science Methods

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Gain insight into a topic and learn the fundamentals.
4.7

356 reviews

Beginner level
No prior experience required
Flexible schedule
1 week at 10 hours a week
Learn at your own pace
95%
Most learners liked this course

Gain insight into a topic and learn the fundamentals.
4.7

356 reviews

Beginner level
No prior experience required
Flexible schedule
1 week at 10 hours a week
Learn at your own pace
95%
Most learners liked this course

What you'll learn

  • Examine the history and current challenges faced by Social Science through the digital revolution.

  • Configure a machine to create a database that can be used for analysis.

  • Discuss what is artificial intelligence (AI) and train a machine.

  • Discover how social networks and human dynamics create social systems and recognizable patterns.

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Assessments

5 assignments¹

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Taught in English

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This course is part of the Computational Social Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

This course gives you an overview of the current opportunities and the omnipresent reach of computational social science. The results are all around us, every day, reaching from the services provided by the world’s most valuable companies, over the hidden influence of governmental agencies, to the power of social and political movements. All of them study human behavior in order to shape it. In short, all of them do social science by computational means.

In this course we answer three questions: I. Why Computational Social Science (CSS) now? II. What does CSS cover? III. What are examples of CSS? In this last part, we take a bird’s-eye view on four main applications of CSS. First, Prof. Blumenstock from UC Berkeley discusses how we can gain insights by studying the massive digital footprint left behind today’s social interactions, especially to foster international development. Second, Prof. Shelton from UC Riverside introduces us to the world of machine learning, including the basic concepts behind this current driver of much of today's computational landscape. Prof. Fowler, from UC San Diego introduces us to the power of social networks, and finally, Prof. Smaldino, from UC Merced, explains how computer simulation help us to untangle some of the mysteries of social emergence.

In this module, you will be able to examine the history and current challenges faced by social science through the digital revolution. You will be able to discuss the mystery at the core of society: social emergence. You will be able to recall the fundamental building blocks of the scientific method and how they apply to the new computational tools we now have available. You will be able to defend what people mean when they say that ‘social studies’ are currently maturing to become a ‘real science’.

What's included

14 videos3 readings1 assignment2 discussion prompts

14 videosTotal 124 minutes
  • What is this Specialization About? (intro to 5-course Specialization)18 minutes
  • Course Introduction5 minutes
  • Optional: Study Suggestions (not required)17 minutes
  • Module 1 Introduction3 minutes
  • The Digital Revolution14 minutes
  • First Ever UC-wide Online Course2 minutes
  • A Very Short History of Science5 minutes
  • A Very Simplistic Hierarchy of Science6 minutes
  • Social Emergence (Part 1)4 minutes
  • Social Emergence (Part 2)7 minutes
  • The Scientific Method Revisited13 minutes
  • Limitations of Induction and Deduction15 minutes
  • Glass of Red Wine Theorizing6 minutes
  • Social Science Challenges8 minutes
3 readingsTotal 30 minutes
  • About UCCSS10 minutes
  • A Note From UC Davis10 minutes
  • Optional/Complementary10 minutes
1 assignmentTotal 45 minutes
  • Module 1 Quiz45 minutes
2 discussion promptsTotal 20 minutes
  • Learning Goals10 minutes
  • Computational Social Science10 minutes

In this module, you will be presented with an example of how computational social science is applied in the real world through a case study. You will be able to discuss examples of digital footprint and describe how computational social science is applied. You will practice an activity and be able to configure a machine to create a database that can later be used for analysis.

What's included

7 videos3 readings2 assignments1 peer review

7 videosTotal 75 minutes
  • Introduction to Examples of CSS (Part 1)1 minute
  • Overview of Big Data10 minutes
  • Fighting Poverty with Data7 minutes
  • Extracting Features9 minutes
  • Predicting Poverty10 minutes
  • Who Cares?9 minutes
  • Webscraping Lab How-To29 minutes
3 readingsTotal 30 minutes
  • Welcome to the Web Scraping Lab10 minutes
  • Welcome to Peer Review Assignments!10 minutes
  • Optional/ Complementary10 minutes
2 assignmentsTotal 50 minutes
  • Web Scraping Assigned Task5 minutes
  • Module 2 Quiz45 minutes
1 peer reviewTotal 60 minutes
  • Web Scraping Lab60 minutes

In this module, you will be able to discover how artificial intelligence can convert news stories into a real-time observatory of global unrest and potential terror attacks, and how brain scans can be used to reveal aspects of your moral values. You will be able to practice interacting with artificial intelligence that can interpret your art skills.

What's included

7 videos1 reading1 assignment1 discussion prompt

7 videosTotal 39 minutes
  • Introduction to Examples of CSS (Part 2)2 minutes
  • Overview of Artificial Intelligence (Part 1)5 minutes
  • Overview of Artificial Intelligence (Part 2)8 minutes
  • Machine Learning6 minutes
  • Overfitting4 minutes
  • Training, Validation, Testing8 minutes
  • A Common Difficulty in ML6 minutes
1 readingTotal 10 minutes
  • Optional/Complementary10 minutes
1 assignmentTotal 30 minutes
  • Module 3 Quiz30 minutes
1 discussion promptTotal 45 minutes
  • Artificial Intelligence: music45 minutes

In this module, you will be able to discover how social networks and human dynamics create systems that are larger than you and me: social systems. You will be able to discuss how social networks and human dynamics follow recognizable patterns. You will be able to identify how social network analysis and computer simulations are currently quite successful in untangling some of the mysteries of social emergence.

What's included

10 videos1 assignment1 discussion prompt

10 videosTotal 67 minutes
  • Introduction to Social Networks and Computer Simulations1 minute
  • Overview of Social Networks10 minutes
  • Connected3 minutes
  • From Obesity to Generosity8 minutes
  • Get Your Friends Involved!9 minutes
  • Overview of Computer Simulations11 minutes
  • Models7 minutes
  • Why Model?6 minutes
  • Cultural Boundaries9 minutes
  • Course Summary1 minute
1 assignmentTotal 45 minutes
  • Module 4 Quiz45 minutes
1 discussion promptTotal 10 minutes
  • Self-Reflection10 minutes

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Instructor

Instructor ratings
4.8 (121 ratings)
University of California, Davis
10 Courses97,892 learners

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Showing 3 of 356

VM
·

Reviewed on Apr 21, 2020

Got a rudimentary level understanding of the power of computational tools like ML, SNA and ABM can help in analysis of human dynamics

NA
·

Reviewed on Aug 6, 2022

Great lectures and quite nice foundation for starting this field, recommendation.

PT
·

Reviewed on Jul 11, 2020

This is a great course to take as an introduction to Computational Social Science. I hope the rest of the Specialization is just as engaging, relevant, and informative.

Frequently asked questions

These are some of the reflections shared by students who have worked through the content of the Specialization on Computational Social Science:

  • "Highly enjoyable and most importantly, giving me exceptionally important skills to fulfill my job requirements at a new position in Munich. You may be interested to know the impact of your course on salary and in my case, the knowledge and certification gained adds about another Euro 20.000 on the annual salary (taking it to about Euro 120.000 p.a.)."

  • "My overall impression of this was: I can't wait to use this for other stuff!!"

  • "I absolutely think that these tools could be used in my future jobs, or even as a personal reflection. If you scrape and analyze the comments/reactions that your business gets on Youtube, Twitter, Instagram, etc., what does their language use say about how they interact with your brand — or what your brand brings out in them?"

  • "Wow, this is cool and fun stuff. Even though I may not pursue anything social-science related in the near future, it is still nice to learn and get to experience all of these tools that computational social science offers and benefits in all kinds of careers and fields of study."

  • "I particularly enjoyed the web-scraping for some reason. It feels very advanced although its very easy. ...It seems to be a very fast and efficient way of grabbing data."

  • "I enjoyed playing around with machine learning! ...It was also amazing to me how quickly it was able to grasp and learn our input in seconds. It makes me wonder how much more technology will advance in these next few years... It's scary but fascinating."

  • "The fact that these tools are so easily usable and attainable is incredible in my mind. Not only do we have access to them like we have access to things like Facebook and Twitter, but they're FREE."

  • "The most interesting aspect was the fact that these tools are all free and online. In the past, only researchers at well-funded universities had access to programs like the ones we used in all of our labs. But now, even someone without much technical knowledge on complex software can use these tools."

  • "I am so surprised that these tools are available to anyone through a simple download, and even more so that they are very user friendly and easy to learn how to navigate. I plan on starting a clothing line company in the future and I think it will be really helpful for me to be able to analyze so much online data."

  • "As an Environmental Policy Analysis and Planning major, I was fascinated to learn that there is a feasible way to simulate policy implementation and impact multiple times within a short span of time."

  • "UCCSS has allowed me to feel more confident in my abilities with a computer and to better understand companies like Facebook or Twitter. ...these tools really are powerful but also dangerous. ...It allows powerful individuals to manipulate ideas."

  • "Throughout the course, the content was challenging, but when it was finally applied to the labs at the end of each module, it was really rewarding to see everything play out. It was even more rewarding when it made sense too! ... I'm really glad I took this course! It was definitely a challenge, but I'm glad I got to experience and learn about so many topics I never knew even existed."

  • "It was fun seeing the results of the code that I made, and I never thought that I would be doing something like this in my life. The results also showed me what the society would look like.... Social network analysis and web scraping could be the tools that I use in my future job as all the internship that I'm looking now all related to social media or digital media."

  • "My career aspiration is to be a digital marketing expert. These computational tools have enormous implications for the field."

  • "I really really loved that this class let me learn hands-on and gave me experience with tools that have real world application and combine STEM & social science. I think that a lot of these tools are useful far beyond homework activities."

  • "Best course I have taken. I wish more online courses structured like this would be offered."

This Specialization on Computational Social Science is the result of a collective effort with contributions from Professors from all 10 campuses of the University of California. It is coordinated by Martin Hilbert, from UC Davis, and counts with lectures from:

1) UC Berkeley: Joshua Blumenstock, Prof. iSchool; Stuart Russell, Professor of Computer Science and Engineering.

2) UC Davis: Martin Hilbert, Prof., Dpt. of Communication & Seth Frey, Prof., Dpt. of Communication & Cynthia Gates, Director of the IRB.

3) UC Irvine: Lisa Pearl, Prof. Cognitive Sciences.

4) UC Los Angeles: PJ Lamberson, Assistant Prof. Communication Studies.

5) UC Merced: Paul Smaldino, Prof. Cognitive and Information Sciences.

6) UC Riverside: Christian Shelton, Prof. Computer Science.

7) UC San Diego: James Fowler, Prof. Global Public Health and Political Science.

8) UC San Francisco: Maria Glymour, Associate Prof. School of Medicine, Social Epidemiology & Biostatistics.

9) UC Santa Barbara: René Weber, Prof. Dpt. of Communication & Media Neuroscience Lab (with Frederic Hopp).

10) UC Santa Cruz: Marilyn Walker, Prof. Computer Science, Director, Computational Media.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.