Overview
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.
Syllabus
- Computational Social Science (CSS)
- 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’.
- Example of Computational Social Science: Data Science
- 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.
- Examples of CSS: Machine Learning & AI
- 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.
- Examples of CSS: Social Networks and Computer Simulations
- 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.
Taught by
Martin Hilbert
Tags
Reviews
4.7 rating, based on 131 Class Central reviews
4.7 rating at Coursera based on 340 ratings
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I really enjoyed this course and learned a lot of valuable concepts. My main criticism--and this just may be because of my particular learning goals--was that I didn't learn to DO as much I'd hoped. The data scraping lab was the kind of stuff I wanted to learn. I understand that extracting data, building models, and mapping data all also require theoretical background. However, for my particular goals I'd have liked to have done more application. Perhaps there are other courses that do that which I'll enjoy even more now that I have a good overview of the theory.
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I’m so confused by all the glowing reviews of this course. Am I taking a different course than everyone else? Perhaps my style of learning differs from most, but I’ve found this course ridiculous at times (with multiple in-video quiz answers revol…
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so far so good, It's an introductory course which introduces a lot of concepts . Let's hope there are more lab and hand-on tutorial and practical skill which i can apply in real life
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I very much like the format, the collaborative contribution of the various experts in this intertwined field. The only change I would recommend for future iterations or similar efforts (not always possible but was the only real technical issue I n…
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This course gave me an overview of the computational social science. The most impressive part is the graph describing different kinds of research and their locations, and tools to deal with these research categories. This is a super nice start and fire up my interest to explore more in CSS. I'm looking forward to the new course!
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For new learners, this course is helpful due to its easy and clear way of dissemination of knowledge. The credit goes to teachers and to coursera for providing such a platform to learn something new at minimal charges. Additionally, it is good to teachers who want to interact in case of doubts. References are also helpful.
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Perhaps the graphics in the presentations are a little cheap, but I can tell a lot of effort was put into this course to actively engage students, which is typically difficult for coursera courses.
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The course was engaging and informative. Loved all of the examples and real world explanations. Hands on exercises and quizzes helped to reinforce the materials.
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It was so dinamic and fun. now i'm very interested on the computacional social science methods like the models or the patterns in the big data por example. Thank you.
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An excellent course to enter the field of Computational Social Science. Even if one doesn't end up in this field, it gives a fascinating insight into how society works in general. I really liked the hands on approach. The examples used in the lectures were perfect!
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That is the best course I have ever took through Coursera. Professors are very very enthusiastic about what they teach, course content, links, quizzes, and assignments (peer-reviewing and web scraping) are highly helpful and informational. I felt li…
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I highly recommend the Computational Social Science Methods course offered by the University of California, Davis via Coursera. The course provides a comprehensive overview of various computational methods used in social science research. The lectures are engaging and informative, and the assignments are challenging yet rewarding. Overall, this course is a great opportunity to enhance your research skills and learn new techniques in the field of computational social science.
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This is a rather intense course. There is a lot of information to take in, especially if you complete all the optional/complimentary materials (there is an entire textbook to read at the end of module 1!). However, it is worth it. I have thoroughly…
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The course provides an excellent overview on Computational Social Science, focusing on Machine Learning and Artificial Intelligence. In addition, the professors offer a great class about methodology. I am a Social Science student, so this course was really interesting to understand the development of technology with humanities.
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This systematically assesses how possible computation helps us advancing social science. Computational methods being mapped out onto three strands of social science: empirical, analytical, and theoretical. Examples given by the tutors are not only articulating but also inspiring due to its counterintuitive nature.
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The content is really informational and easy to understand for begineers. This course is like a summary of what we willl learn throughout the specialization. However, the free version is really limiting in ters of not just inacessibility to quizes but also to hands on learning experiences.
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Excellent course to have a high level understanding of what Computational Social Science (CSS) is and the methods used in the field including Machine Learning, Social Network Analysis, Agent-Based Simulations among others. The course provides many…
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Learned a great deal - the rate of change in the existence and use of big data is astounding. Course provides an excellent backdrop to how Big Data is actually being used.
- On a positive note, to understand human behavior - how we are connected and to see how how there are patterns never previously seen clearly.
- On a more intrusive note - welcome 1984 - to understand how, for example, Facebook, Google, the political parties, and others, influence us on levels we never even realized, using information that we never fully appreciated that they have.
I can wholeheartedly recommend this course and share that I enjoyed it very much.
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Excellent introductory course on Computation Social Science. Overviews the concepts and includes history of social science and ties it all together. A good starter to understand the importance of social science. Thank you.
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I particularly enjoyed the web-scraping for some reason. It feels very advanced although it's very easy. ...It seems to be a very fast and efficient way of grabbing data. Throughout the course, the content was challenging, but when it was finally applied to the labs at the end, 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. These computational tools have enormous implications.