Your grade is divided into 3 components:
There are no minimum grades in any of the evaluation components, but failure to present any of the deliverables (homeworks, test, presentation and project) will result on a RFF evaluation (the student essentially did not participate on the course) and failure to present the project will result on a RFC evaluation (missing a component).
Homeworks: small group (max: 2 persons) homeworks (at least 2 week for each) to be delivered by email. You will apply some concepts in practice (potentially using a computer to analyze small datasets).
Mini-Test: one small individual test (pen and paper) to be done "on site" during monday class. The test will be scaled to 1h30m and you will be given +30m of extra time.
Tentative Dates:
Type: individual presentation
Date of presentations: towards end of semester
Time for each presentation: 10 to 20 minutes
Delivery Format: video presentation
This is an individual assignment. Students should select a recent scientific article (preferably year of publication >= 2017) 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.
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 three students
Limit for project delivery (article): end of classes
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: