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Learner Reviews & Feedback for Network Dynamics of Social Behavior by University of Pennsylvania

4.6
stars
386 ratings

About the Course

How do revolutions emerge without anyone expecting them? How did social norms about same sex marriage change more rapidly than anyone anticipated? Why do some social innovations take off with relative ease, while others struggle for years without spreading? More generally, what are the forces that control the process of social evolution –from the fashions that we wear, to our beliefs about religious tolerance, to our ideas about the process of scientific discovery and the best ways to manage complex research organizations? The social world is complex and full of surprises. Our experiences and intuitions about the social world as individuals are often quite different from the behaviors that we observe emerging in large societies. Even minor changes to the structure of a social network - changes that are unobservable to individuals within those networks - can lead to radical shifts in the spread of new ideas and behaviors through a population. These “invisible” mathematical properties of social networks have powerful implications for the ways that teams solve problems, the social norms that are likely to emerge, and even the very future of our society. This course condenses the last decade of cutting-edge research on these topics into six modules. Each module provides an in-depth look at a particular research puzzle -with a focus on agent-based models and network theories of social change -and provides an interactive computational model for you try out and to use for making your own explorations! Learning objectives - after this course, students will be able to... - explain how computer models are used to study challenging social problems - describe how networks are used to represent the structure of social relationships - show how individual actions can lead to unintended collective behaviors - provide concrete examples of how social networks can influence social change - discuss how diffusion processes can explain the growth social movements, changes in cultural norms, and the success of team problem solving...

Top reviews

PA

Jul 28, 2019

This course really enhanced my understanding of collective intelligence, however, it would be great if instructors provide lecture slides also to revise the course whenever required.

SC

Jan 20, 2018

A Crisp yet effective overview of some of the most critical works in the field of Networking. Anyone from the fields of Management, Sociology, Anthropology et al should try the MOOC.

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1 - 25 of 95 Reviews for Network Dynamics of Social Behavior

By Guilherme S T

Oct 4, 2019

Really interesting course. Would be interested in a more complete one with the mathmatical modeling. One thing bothered me. They don't use the concept of complexity as the more recent literature uses (see

Emilian Kavalski work). A rocket is a extremely complicated thing but it is not complex, because you can study the parts and undertand the hole. Tou can't do that with a complex system, like global economy or global govermnance

By Navaneethan S

Jun 15, 2018

The course discussed some absolutely fascinating material - I really enjoyed learning about Schelling Segregation Model (collective dynamics are not obvious from individual preferences), how dense local connections are necessary for spreading behaviours that require social reinforcement (which initially seemed counterintuitive), and the section on problem solving in networks.However, I felt that the material was quite superficial in its treatment - the quizzes were very straightforward and didn't require a really deep understanding of the material (in my opinion), nor was there much attention paid to the maths underlying these phenomena. While I understand that this may not have been the aim of the course (since equations tend to put of people less comfortable or uninterested in mathematical detail), it would have been nice if the Resources contained links to further reading for those interested.Alternatively, it would have been really wonderful if Josh or Damon (both of whom explained the material really well), had added optional videos going into the material - this is how Andrew Ng does it in his Deep Learning course, and I found that extremely helpful.Overall, I would definitely recommend this course to everyone interested in a radically different approach to understanding human behaviour!

By Muru Z

Nov 10, 2019

Although the model has some flaws which I'm considering about, it's a good course for introducing how to use a computational model to model the phenomenon in social networks and predict collective behavior. I have read some books about the complex systems and I'm also majoring in computer science, I do believe the research on collective behavior is a key point on understanding the world and I'm fascinated by it. Thanks for the tool this course introduced to me and for the content it shows! Thanks for the good lectures the professor gave me!

By Jean-Philippe C

Jan 15, 2018

I think this course is VERY interesting ! Very nice simulations are demonstrated and very great teachers. The results of simulations are striking ! Yet, as a physicist and computer scientist, I would have prefer more math for the modeling part. I will look for that on my own. I recommend this course for everyone who has interests in social dynamics and modeling (and to some extent applied game theory).

By Ada L

Mar 21, 2020

I have never learned agent model in social network courses in graduate school. This course brings me up to date about the aggregate effects of unintended individual behaviors

By Agata S

Mar 21, 2021

Extremely interesting course. I've been working on social norms and this has added greatly to my understanding of norms and other related phenomena. I'd highly recommend it.

By pranav n

Sep 5, 2018

needs more practical exercises

By Yijun C

Jul 14, 2020

As far as I am concerned, this course is helpful. It gives me some understanding of social behaviours from a higher level. For example, social norms can not only be regulated by centralised authorities but also be naturally formed by people involved in social network (our society). Additionally, it talks about how network structure can affect the contagion. Also, different kinds of contagion will have different performances in the same network structure. However, the contents of this course doesn't include extract mathematical model. I hope it can tell us something related to math, which could explain the social phenomenon in a more analytical way in the next version!

By 赵志豪

May 6, 2021

On the whole, it is still too simple. The explanations in the first four weeks are clear and easy to understand, while the fifth week is rather vague. After-class tests tend to be conceptual. None of them have a holistic understanding of network dynamics, which is slightly disappointing.

By Kipkem H

Jun 14, 2020

Course was quite interesting and what seemed intuitive at first did not pan out the way I expected. Challenging introduction to Network Dynamics and can see if I had downloaded and used software along with using mathematical models, it would have been more challenging.

Writing this June 2020 and it will be helpful to use aspects of this course for the coronavirus disease 2019 (COVID-19) pandemic [spread worldwide, outcomes within and among different states, mitigation strategies and their effectiveness].

By Jarryd G

Jun 27, 2019

This course was mind blowing. After you start to understand the foundational aspects of week 1 and week 2, they really ramp it up into some applicable real-world scenarios. The information that I have heard and reinforced in this course will make a huge impact to the way that I go about working with change in my job. I am extremely thankful for these resources as they are of great quality, well delivered by Damon and Josh, and with great visuals and examples to go with them.

By Jonathan S

Sep 14, 2019

The course was truly fascinating .. providing insights into processes of information transmission and disease diffusion, how people adopt social conventions, and the best social organization of research and design activities, all though the lens of social network structure. The courses uses simple computational models (no programming required). I learned a great deal and really want to explore this approach further.

By 김채연

Feb 17, 2018

i started this course after i read a book 'Linked' and became interested in network science. Although English is foreign language to me and Netlogo is new to me, i didn't have any difficulties understanding the course because it contains lots of examples and easy explanations. and i'm satisfied as i learned how social network works in our society. Thanks!

By Thiago E

Dec 13, 2018

Insightful, packs a lot of information in a deceivingly simple manner. Challenges intuition with proper models and raises as many (if not more) questions than it answers, which couldn't be any better as fuel for learning. Thumbs up, and would love to see more and more in-depth material on the theme from the instructors.

By Sonia L

Oct 22, 2018

Congratulations to the team for the simplicity with wich they have been able to transmit complex concepts. I am amaze of how some social assumptions change when you model them. I have learn a lot and created more curiosity to continue investigating about network dynamics of social behavior.

By David B

Jul 19, 2018

Nice approach to understand different aspects of the study of social networks dynamics, with good examples. I think it would be interesting to see the specifics of the rules of behavior of the second half of the course, like the specifics of the genetic algorithm. Great course !

By Angeline T

Nov 27, 2017

Extremely interesting class. It gave me deep insights on social behavior, trend spreading patterns and how connectivity relates not only to behavior, but also culture, performance. I'll definitely use NetLogo by myself and am looking forward to learn more and experience more.

By Sarah L D

Jan 22, 2018

As an undergrad communication student, I am consider using this information and more research on Network Dynamics of Social Behavior as the basis for my honors capstone. This course helped me discover part of communication research I want to delve deeper into.

By 정소현

Jun 30, 2019

This was an excellent course. The key contents was prepared and delivered very well, and I was able to learn the basics of the topic. I think I've found a topic I'd like to major in for my masters... so a big thank you to the faculty members at U Penn! :)

By Amy S

Jan 18, 2018

Excellent course. I found the videos to be packed pretty full and sometimes had to watch more than once to make sure I'd really mastered all the material. That's a good thing, though! I learned a lot and found the course very thought-provoking.

By sonia

Oct 15, 2019

Great introduction to the subject of complex social systems. Sparked a lot of thinking on social networks, spreading of information and the dynamics of social change. looking forward to a follow-on course on the subject.

By Zachary E

Jul 7, 2019

An extremely interesting and thought-provoking.introduction to models for social network dynamics and their results. Would love see a follow-up that takes a more in-depth look at the mathematics behind the models.

By Pieter V B

Feb 1, 2024

I don't usually leave these reviews, but this is one of the best put together courses on this platform. The visual and textual presentation is top notch and makes for such a smooth learning experience.

By Poornima A

Jul 29, 2019

This course really enhanced my understanding of collective intelligence, however, it would be great if instructors provide lecture slides also to revise the course whenever required.

By Shantanu C

Jan 21, 2018

A Crisp yet effective overview of some of the most critical works in the field of Networking. Anyone from the fields of Management, Sociology, Anthropology et al should try the MOOC.