Computation + Journalism Class at Georgia Tech

Catalog Description

This class is aimed at understanding the computational and technological advancements in the area of journalism. Primary focus is on the study of technologies for developing new tools for (a) sense-making from diverse news information sources, (b) the impact of more and cheaper networked sensors (c) collaborative human models for information aggregation and sense-making, (d) mashups and the use of programming in journalism, (e) the impact of mobile computing and data gathering, (f) computational approaches to information quality, (g) data mining for personalization and aggregation, and (h) citizen journalism. Complete schedule and other information will be on the t-square site available to only students taking the class.

Instructor

• Irfan Essa (irfan at cc dot gatech dot edu). Email is the best way to get a hold of the instructor, if class related make sure to add CJ2012 in the subject line. For more information go here. Office hours after class, and can be scheduled via email.

TA

• Yachna Sharma (ysharma3 at gatech dot edu). Office hours can be scheduled via email OR will be announced as needed.

Books

• [K&R] Bill Kovach and Tom Rosenstiel (2007). The Elements of Journalism: What Newspeople Should Know and the Public Should Expect. 2007. Three Rivers Press. (Amazon)
• [PM] Philip Meyer (2002) Precision journalism: a reporter’s introduction to social science methods. 2001. Rowman & Littlefeild (Google Books)

Grading

Both the UG section (CS 4464) and the Grad section (CS 6465) will meet together and share every effort, except one. Grad students will be required to lead and critique a paper or a journalism project or site in class and with a report (10 min presentation).  Each group will be compared separately for final grade assignments.  (Some of the following, subject to slight modifications as the term unfolds).

CS 4464

• Assignments 1, 2, 3 (33%, 11% each)
• In class and written paper presentation or a critique of a journalism effort/site. (8%)
• Class and Online Participation (15%)
• Review of Assigned Readings before EACH Class (12%)
• Final Project 32%
  • Includes, Proposal (3%), 2 Updates (4% each, 8%), Presentation/Demonstration(10%), Report (8%) and Self-Evaluation (3%)

CS 6465

• Assignments 1, 2, 3 (33%, 11% each)
• In class and written paper presentation or a critique of a journalism effort/site. (8%)
• Class and Online Participation (11 15%)
• Presentation in Class of one of the papers (4%)
• Review of Assigned Readings before EACH Class (12%)
• Final Project (32%)
  • Includes, Proposal (3%), 2 Updates (4% each, 8%), Presentation/Demonstration(10%), Report (8%) and Self-Evaluation (3%)

Topics to be COVERED in this class include:

• Overview of Journalism and Computational Disciplines
• Elements of Journalism
• Journalism is a (Social) Science
  • Precision Journalism
  • Investigative Reporting
• News Gathering and Mobile Technology
  • Mobile Computing for news
  • People as Sensors: Citizen Journalism, Implications
  • Citizen Journalism
• The Theory of Reporting and how computation participate
  • Storytelling with a Purpose
  • Contextualization & Sense-making
  • Information Quality, Bias in Reporting, Journalistic Values
• The Practice of Reporting and the impact of Computing
  • Different Types/Styles of Reporting
  • The Blogsphere and Reporting
  • Citizen Journalism
  • Web 2.0, Semantic Web and WEB Science
  • Social Networking and Dynamics and NEWs / DATA collection.
  • Automated Reporting and Programming in Journalism
  • Generation of Newscasts and Documentaries
  • Mashups: Webservices, Online Data Sources
  • Investigative Programming
• Computational Analysis of News Archives
  • Web Crawling / Scraping
  • Sentiment Analysis
  • Topic Detection and Tracking (Entity Extraction)
  • Video Analysis
  • Computational Linguistics and Natural Language Processing (NLP)
• Visual Design, Illustration, and Visualization of News
  • Visual Communication and Information Design
  • Visualizing News Information
• News Aggregation / Summarization / Personalization
  • Value Added Information Science
  • Models: Open Source (Wikification), Editor Based, Mixed
  • Automated Aggregation/Clustering vs. Person Powered Aggregation
• Editing/Credibility/Authority/Reliability
  • Authoring, Authority, Credibility
  • The Role of the Editor, How is the web changing that.
• Image and Video Manipulation
  • Tools / Techniques for Manipulation
  • Manipulation Detection and Digital Forensics
  • Ethics
• News Consumption and Distribution
  • Interactivity: Not Just Consumption
  • Audience and Audience Measurement
  • Distribution Models, Media, Technologies
• Advertising and the News
• News Gaming
• Legal Aspects
• Ethics / Morality / Subjectivity
• Media Monitoring
• Information Accessibility
• Sensemaking
• Networked Journalism
• Syndication
• Information Science
• Reputation / Recommender Systems