Your grade is divided into 3 components:
There are no minimum grades in any of the evaluation components, but failure to deliver and present the project will result on a RFC evaluation (missing an evaluation component).
2 individual homeworks (around 4 weeks for each) to be delivered by email. You will apply some concepts in practice (potentially using a computer to analyze small datasets). You can discuss with me if you have difficulties when trying to do the homework
Type: individual presentation (video recording)
Selection of article: 20th June
Delivery of video: 27th June
Expected Duration of video: 10 to 20 minutes
This is an individual assignment. Students should select a recent scientific article (preferably year of publication >= 2016) about network science and should carefully read it so that they can present it orally to the other students and to the instructor. You should produce a small set of slides to assist you on the presentation and record a video presentation that you send to your professor.
You should select a topic that interests you. The paper could be about a method, a model, an application, or any other subfield, as long as its core data being analyzed is of network type. When you have selected an article, please contact me so that I can validate your choice.
You can look for articles on specific topics using academic search engines such as Google Scholar or Semantic Scholar.
Here are a few examples of journals/conferences where you can find related articles:
Since Network Science is a multidisciplinary area, there are many excellent related articles on conferences with a more broad range of topics. For example:
You can also look at some "big" Network Science names and their recent papers:
Type: individual or groups of two students
Limit for project delivery (article): 25th of July
Students will need to present the following deliverables:
The basic idea is for you to work on a small scale project in which you will analyze a network dataset using the concepts you learned in the course.
You could either use already existing datasets, or create a new one (see the useful links section for some existing network datasets). In the same way, you can use already existing software tools or use your own code.
You can also focus more on the analysis in itself (ex: showing insights gained), on the efficiency of the implemented algorithms (ex: showing execution times on different datasets), or on any other combination.
You are strongly encouraged to speak with the professor so that you can validate your idea for the project before starting your work.
Here are some example projects: