INFO I400-I590: Performance Analytics
Prof. Filippo Radicchi
filiradi@indiana.edu
http://filrad.homelinux.org





Description.

In social systems, there is competition for prestige, 
recognition, awards, social status, popularity, 
leadership, wealth, fame, etc. What makes the difference 
in the achievement
of these objectives? Is there any pattern behind success?
For example, why an hashtag on twitter
becomes popular, a song enters the hit parade,
or a scientific paper becomes highly cited?
This course will review quantitative studies
aimed at measuring, predicting and understanding
performance in social competitive arenas, ranging 
from social media to financial markets, from 
professional sports to scientific and 
technological innovation.  




Aims.

Students will learn:

- how to retrieve and extract performance data
from the web or other electronic resources;

- how to measure and characterize performance
from data with statistics and complex network theory;

- how to generate models for performance prediction.



Evaluation.

Participation: 20%.
Based upon attendance and participation.

Presentation and Discussion: 30%.
Students will present and lead the discussion of an article 
related to the class materials. This includes 
presenting concepts necessary to understand the article.

Project or Term Paper: 50%
Depending on background, students will either tackle 
a real problem or write a term paper. In either case, students 
are expected to continuously consult with the instructor 
regarding the scope and depth of the project or paper.
Collaborative research projects are allowed. 



Main topics covered in the course.

- Performance in professional sports

- Scientific impact

- Technological innovation

- Popularity in social media

- Measures of performance in financial markets




Prerequisites.

- basic knowledge of programming (e.g., python, perl)

- basic knowledge of statistics