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University of California, Davis

Computational Social Science

University of California, Davis via Coursera Specialization


For more information please view the Computational Social Science Trailer Digital technology has not only revolutionized society, but also the way we can study it. Currently, this is taken advantage of by the most valuable companies in Silicon Valley, the most powerful governmental agencies, and the most influential social movements. What they have in common is that they use computational tools to understand, and ultimately influence human behavior and social dynamics. An increasing part of human interaction leaves a massive digital footprint behind. Studying it allows us to gain unprecedented insights into what society is and how it works, including its intricate social networks that had long been obscure. Computational power allows us to detect hidden patterns through analytical tools like machine learning and to natural language processing. Finally, computer simulations enable us to explore hypothetical situations that may not even exist in reality, but that we would like to exist: a better world. This specialization serves as a multidisciplinary, multi-perspective, and multi-method guide on how to better understand society and human behavior with modern research tools. This specialization gives you easy access to some of the exciting new possibilities of how to study society and human behavior. It is the first online specialization collectively taught by Professors from all 10 University of California campuses.


Course 1: Computational Social Science Methods
- Offered by University of California, Davis. This course gives you an overview of the current opportunities and the omnipresent reach of ... Enroll for free.

Course 2: Big Data, Artificial Intelligence, and Ethics
- Offered by University of California, Davis. This course gives you context and first-hand experience with the two major catalyzers of the ... Enroll for free.

Course 3: Social Network Analysis
- Offered by University of California, Davis. This course is designed to quite literally ‘make a science’ out of something at the heart of ... Enroll for free.

Course 4: Computer Simulations
- Offered by University of California, Davis. Big data and artificial intelligence get most of the press about computational social science, ... Enroll for free.

Course 5: Computational Social Science Capstone Project
- Offered by University of California, Davis. CONGRATULATIONS! Not only did you accomplish to finish our intellectual tour de force, but, by ... Enroll for free.


Taught by

Martin Hilbert


4.8 rating, based on 129 Class Central reviews

Start your review of Computational Social Science

  • Great introductory course on Computational Social Science, a fairly new and exciting feel of Social Science.

    Martin Hilbert gives a great overview of the computational techniques and social theories that Computational Social Scientists use in their work, from empirical to the analytical, and from theories to simulation.

    The course length is sweet, and the material given isn't difficult to understand, although it requires some basic familiarity with maths and using computers.

    This course should be taken by anyone who is interested in the field of Computational Social Science.
  • It gave bird eye view on several of the topics lab work was little improved than previous courses in the specialization
  • Anonymous
    A well structured course, with lectures that are clear and relevant. There is a lot of theory easily explained by providing examples that allow students with different backgrounds to follow without problems the curricula. As a compliance & ethics professional, I highly recommend it as opened my eyes to methodologies and tools I could use for my work.
  • Anonymous
    Great course, I´m studying my Phd, and this course has help me to understand the complex network. I hope to be able to advance in the following modules and courses that you have
  • Profile image for Minjoo Lee
    Minjoo Lee
    This course exceeded my expectations tremendously! I was able to learn from professors from every UC campus which gave me expertise knowledge in every area. When I signed up for the course I immediately understood that this course is perfect for peo…
  • Anonymous
    I'm excited to go through the course! It was an amazing adventure to the world of CSS, machine learning, scientific approaches - induction and deduction, agent based modelling and web scraping. I was able to apply the knowledge I got in this course…
  • Anonymous
    It was a very good course for getting to know the topic of social network analysis and I recommend it. This course does not go deep in any way and very quickly and superficially reviews all the topics in this field, and while it does not take much of your time, it gives you an almost complete view of this field.
  • Anonymous
    Awesome class! I took it as a UCD student to fill my units in my senior year, turned out I believe this may be one of the best classes to take as a freshman/transfer just yet! Very good intro to different topics in CSS and introduce different possible applications to AI, no coding/math background required for this course, but of course it can lead to very coding/math-intense course if you find it interesting enough to do it for a living. A bit time-consuming for a filler class, but strongly recommended who wants to take a sneak peak in the AI world.

    Bonus: the professor is German, so his German humor is a bit of a highlight. It's the kind of joke that you want to laugh but it's hard to laugh, I loved it.
  • Anonymous
    For me as a social science researcher this specialization was an interesting window to the new achievements of computer scientists in social research. I think in making a new intersection between sociology tradition and these new approaches we are just at the beginning.
  • Anonymous
    I welcomed the detailed analysis of how networks can be built and how they work. Nevertheless, I would have appreciated more concrete examples from the current social media networks, to illustrate the analysis.
  • Anonymous
    Was a good course I learn a lot about SNA Big Data and how use web scrapping to apply it in Gephi. Also learn how is the composition of network and main concepts, like degrees, in-degrees, out-degrees, and much more.
  • Anonymous
    This is such a beginner-friendly course for people who want to reach out social network analysis/ network analysis. The structure of this course is reasonable, the content is interesting and not shallow.
  • Anonymous
    A great introduction to computational social science methods. Knowledgeable and well-respected professor with a plenty of examples, research to model, and hands-on activities for a practical skill-building.
  • Anonymous
    This was one of the most interesting and informative courses I have taken. If you are interested in Computational Social Sciences, I highly recommend this course!
  • Anonymous
    It was an enjoyable course, very dynamic, clear, and insightful. It also provides practical tools that can be quickly applied to research. Good examples also.
  • Profile image for Babita Kathayat
    Babita Kathayat
    In this course I learned how social networks evolve, how can we analyse the social network . This learning can be utilised to understand the process of how information be it new knowledge, rumours, fake news spreads in a network. I find this course helpful in applying in social sciences research. I also learned data wrangling that is scrapping data from websites and analyses how they are linked in gephi software. I recommend it for its utility in data analysis in research.
  • Anonymous
    I took this course through UC cross enrollment 2 years ago . The course content was very up-to-date, and included guest lectures from professors from a very wide range of disciplines, so it would be interesting to students regardless of their majors. Despite not being a student in the social sciences (my majors are in humanities and arts,) this class has equipped me with a lot of basic digital literacy (e.g, present issues of privacy with photo filter apps, epidemic modeling) that has been helpful in everyday life. I hope Prof. Hilbert can make more of his classes available.
  • Anonymous
    Having taken this course as an undergraduate, I can honestly say that this course effectively simplified complex concepts through practical projects. Computational Social Science might seem 'scary' at first, but Dr. Hilbert managed to provide diverse content, superb guidance, and enough flexibility to be creative to make the learning experience sufficiently challenging and extremely rewarding. Whether you're taking this course as first-timer or seasoned researcher, one can narrow or expand their interests while maintaining a comprehensive learning experience.
  • Anonymous
    This is an excellent course for beginners just learning about computational social sciences, or for those looking to brush up on their knowledge. The course is nicely laid out, with each section featuring an interactive lab relating to social network analysis, that helps you apply what you have learned in a fun, effective way. I highly recommend this course to anyone interested in careers involving social network analysis or human behavior.
  • Anonymous
    The course is interesting for students, who didn’t learn social networks. It provides an opportunity to get acquainted with the basics of building, studying and predicting the development of various social networks. Contains a practical exercise using the Webscraper module and the Gephi program (so it is advisable that you have the opportunity to do this work on a PC).

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