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Вернуться к Анализ социальных сетей

Отзывы учащихся о курсе Анализ социальных сетей от партнера Калифорнийский университет в Девисе

4.7
звезд
Оценки: 111
Рецензии: 31

О курсе

This course is designed to quite literally ‘make a science’ out of something at the heart of society: social networks. Humans are natural network scientists, as we compute new network configurations all the time, almost unaware, when thinking about friends and family (which are particular forms of social networks), about colleagues and organizational relations (other, overlapping network structures), and about how to navigate delicate or opportunistic network configurations to save guard or advance in our social standing (with society being one big social network itself). While such network structures always existed, computational social science has helped to reveal and to study them more systematically. In the first part of the course we focus on network structure. This looks as static snapshots of networks, which can be intricate and reveal important aspects of social systems. In our hands-on lab, you will also visualize and analyze a network with a software yourself, which will help to appreciate the complexity social networks can take on. During the second part of the course, we will look at how networks evolve in time. We ask how we can predict what kind of network will form and if and how we could influence network dynamics....

Лучшие рецензии

VM
7 сент. 2020 г.

This course bringg us with many patience many perspectives and concepts in order to understan social networks. I think it was incredible for my own self-learning, and for my future researches.

MN
15 апр. 2020 г.

Excellent course. Learning a lot about social network analysis. Hope to see some advance courses on this domain.

Фильтр по:

1–25 из 31 отзывов о курсе Анализ социальных сетей

автор: Everett A

27 апр. 2020 г.

Very interesting and unique concepts! The teaching is clear and at a low enough level that everyone can understand; no math or prior social science knowledge is required. However, for the in-video questions that appear, I recommend that you include a picture of what you're referencing in order to answer the question when appropriate. For example, in module 2, there were a few questions requiring us to calculate the degree, closeness degree, etc of a given network. However, the question prompt blocked the view of the network, so I had to rely on memory of the network in question to answer the question. It would've helped if there was a picture of the network in the prompt itself to serve as a reference for us to use to answer the question.

автор: Prof. R V K

25 мая 2020 г.

A very well explained course covering the basics of Social Network Analysis. Only thing I would like like to see more would be the use of Social Network Analysis Software and more practical analysis of the Social Networks. On the overall I thoroughly enjoyed the course and the content. Thanks for the experience. The course is definitely recommended for any beginner in Social Network Analysis.

автор: Thiago P B d M

31 мар. 2020 г.

The course gave me a very good idea about social networks and also ideas to use in the context of social sciences

автор: Miguel C

11 сент. 2020 г.

My favorite course in this specialization - and one of my favorites ever! Once we've understood more theoretical concepts, we could really put it into practice and see real-life applications of this analytical tool as well as theoretical implications via computer simulations. The potential of visualizing social networks is mind-blowing!

автор: Milena

26 июня 2020 г.

Great course for beginners in SNA or scholars exploring new perspectives in computational social sciences. An introduction in a reach, interdisciplinary type of exploratory research that seems to be living up to its full potential in the digital age. Heartily recommending it to those looking for a first taste of SNA.

автор: Jesús P

13 авг. 2020 г.

Es un curso introductorio excelente. El profesor Martin Hilbert presenta las nociones, conceptos y técnicas de una manera sencilla, sin perder rigor y con una visión práctica de los conocimientos. Muchas gracias Coursera y Profesor Hilbert. Ha sido una excelente experiencia de aprendizaje

автор: Guan-Yuan W

31 мая 2020 г.

I really enjoyed this course, I've learnt the software that specializes in SNA which was very interesting. So now I wanna take another course that relates to the social network, in order to further this part of knowledge. Keep learning.

автор: Fernando M

24 июня 2020 г.

Excelente curso, fue todo un reto tratar de entender conceptos difíciles en un idioma que no es nativo para mi, no se hizo pesado seguir el curso y es una ventaja poder retomarlo en los horarios en que uno no está trabajando.

автор: Gonzalo B V

5 июня 2020 г.

Quite interesting course to get an introduction to the analysis of social networks.

The explanations were very good, even if some times I had to review some videos because of the complexity of the subject.

автор: Vladimir A A M

8 сент. 2020 г.

This course bringg us with many patience many perspectives and concepts in order to understan social networks. I think it was incredible for my own self-learning, and for my future researches.

автор: Mr. M K N

16 апр. 2020 г.

Excellent course. Learning a lot about social network analysis. Hope to see some advance courses on this domain.

автор: Matthew P

6 июля 2020 г.

Loved learning the basics and getting hands on using the tools needed to analyze Social Networks. Great Course.

автор: Anran W

11 апр. 2020 г.

A great crack course on SNA. It might be a bit difficult for newcomers, but you are making the right choice.

автор: Mahalakshmi D

22 авг. 2020 г.

Very useful and wonderful course to enhance my knowledge. Looking forward more to learn. Thank you.

автор: mohammad

2 нояб. 2020 г.

Very Usefull. Thank to Mr. Hillbert.

But it can be more technical with more exerciceses.

автор: Domieck

28 мар. 2020 г.

Learned a lot more than expected and Hilbert is a great professor

автор: Diego A P P

6 авг. 2020 г.

Excellent course. Explain very complex concepts in a simple way.

автор: safia s

26 апр. 2020 г.

It is very good course, The instructors are really very good

автор: Sepehr M

18 апр. 2020 г.

Very good. Martin Hilbert is a very good teacher.

автор: Samuel D Z L

7 июня 2020 г.

Genial introducción al tema de redes

автор: Priya Sharma

6 июня 2020 г.

Great Insights. Much Valuable

автор: Siraj M

9 июля 2020 г.

A super cool course for SNA.

автор: GUILLERMO F R R

25 сент. 2020 г.

excellent, very interesting

автор: Yurii S

28 июня 2020 г.

The Best Cours!

автор: Ben B

10 нояб. 2020 г.

Maybe the strongest course in the specialization. You will work with gephi - a good tool for quick network analysis (I still prefer to do it using R or Python, but gephi is easy to use and offers a lot of possibilities and a nice user interface.

Be prepared that your peer-review will take a couple of days.