Who is watching our online activities? How do you protect a source in the 21st Century? Who gets to access to all of this mass intelligence, and what does the ability to survey everything all the time mean both practically and ethically for journalism? In this lecture we will talk about who is watching and how, and how to create a security plan using threat modeling.

Topics: How is email transmitted? Who has access to your emails. Mass surveillance and its legal status. How cryptography works. Encryption versus authentication. Man-in-the-middle attacks. Secure communications using OTR. Case study: the leaked Wikileaks cables. Threat modeling. Security planning.

Instructor: Jonathan Stray
Course blog: jmsc.hku.hk/courses/jmsc6041spring2013/

1. Basics of Computational Journalism: Feature Vectors, Clustering, Projections
2. Text Analysis: Tokenization, TF-IDF, Topic Modeling
3. Algorithmic Filters: Information Overload
4. Social and Hybrid Filters: Collaborative Filtering
5. Social Network Analysis: Centrality Algorithms
6. Knowledge Representation: Structured data & Linked open data
7. Drawing Conclusions from Data
8. Security, Surveillance, and Privacy

Computational Journalism is a course given at JMSC during the Spring 2013 semester. It covers, in great detail, some of the most advanced techniques used by journalists to understand digital information, and communicate it to users. We will focus on unstructured text information in large quantities, and also cover related topics such as how to draw conclusions from data without fooling yourself, social network analysis, and online security for journalists. These are the algorithms used by search engines and intelligence agencies and everyone in between.