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.
Computational Social Science Methods
This course is part of Computational Social Science Specialization
Instructor: Martin Hilbert
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(332 reviews)
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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There are 4 modules in this course
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 quiz2 discussion prompts
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 quizzes1 peer review
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 quiz1 discussion prompt
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 quiz1 discussion prompt
Instructor
Offered by
Recommended if you're interested in Data Analysis
University of California, Davis
University of California, Davis
Johns Hopkins University
University of California, Davis
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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.
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