Opiniones y comentarios de aprendices correspondientes a Network Dynamics of Social Behavior por parte de Universidad de Pensilvania

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!

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

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!

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).

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

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.

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].

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.

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.

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!

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.

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.

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 !

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.

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.

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! :)

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.

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.

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.

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.

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.

A very enjoyable, useful and well crafted course. Should serve well as an introduction to the field and may be useful to people working any number of industries.

This course is a great place to start if you are looking to have some basic understanding of Network Dynamics of Social Behavior

Although the course was very short and the homework were so easy, I'm quite satisfied by the insight I got from Prof Centola

Fantastic course! Very good introduction to network dynamics for someone who has never explored this field of research.