ISE369/POL369
Introduction to Political Informatics
(updated 5/15/2026)

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Course Information

Semester: Spring 2026
Time: Tuesday and Thursday, 12:30PM - 1:50PM
Location/Delivery: In-person and Synchronous Online: direct instruction occurs in real time either in the designated classroom (CS2120) or via a Zoom session. Most sessions are planned to be offered in-person, but some sessions may be held through Zoom if the educational objectives can be better achieved on-line. For any on-line session, an e-mail message will be sent in advance to each student with the URL needed to access the session. Recordings of in-person class sessions will not be made available, so be sure to attend during the regular class hours. Recordings of on-line class sessions will also not be made available, but you will be enabled to record each session once you are admitted into the Zoom session.
Texts
  1. The Politics of Congressional Elections, 11th Edition (or 10th Edition), Jamie L. Carson and Gary C. Jacobson, Rowman & Littlefield Publishers, 2024, ISBN-13: 978-1538176733.
  2. Data Analysis for Political Science, Robert F. Kelly, 2026 (chapters will be provided in class)
  3. Python for Data Analysis, 3rd Edition, Wes McKinney, O’Reilly Media, Inc., October, 2022, ISBN-13: 978-1098104030. (helpful, but not required)

Contact Information

Instructor: Dr. Robert Kelly
E-mail: robkelly@cs.stonybrook.edu
Office hours (Zoom): Mondays, 5:00PM-6:30PM,
Wednesdays, 2:30PM-4:00PM,
but most office hour discussions by Zoom in advance of scheduled hours.
Office location: New Computer Science 218
Piazza https://piazza.com/stonybrook/spring2026/ise369pol369/home

Content

Recent advances in the availability of large data sets, analytic methods, and technology tools have impacted the foundations of democratic society, specifically the ability of elections to provide representation for the underlying population. This course presents the information aspects of these advances. Topics covered include election data capture, election result data sets, gerrymandering, redistricting, micro-targeting, voter surveys, election security, election district geometry, impact of social media, measures of political quality, and the prediction of election results. 

This course is offered as both ISE 369 and POL 369. Successful completion of CSE 101 or CSE114 or IAE101 is required to enroll in this course. Successful completion of one of the following courses is also required to enroll in this course: AMS102, AMS110, AMS310, or POL201. POL102 is an advisory prerequisite of the course. Students enrolling in this course who have not completed POL102 should expect to work harder and possibly not do as well as students who have completed POL102.

Course Outcomes

The outcomes for the course are:

  1. Students will understand the legal and legislative requirements for fair elections.
  2. Students will understand the semantics and processing of data sets used for political analysis and apply that understanding to the processing of actual election data.
  3. Students will combine multiple data sets to analyze the racial and political fairness of election results. 

Interaction

For in-person class sessions, class interaction will be through questions and comments raised in class. For Zoom sessions, class interaction will be provided using the interaction features of Zoom.  For example, during a class students are encouraged to enter any questions using the chat feature. Appropriate questions will be reviewed by the instructor at suitable times during the session, read to the class, and answered. An on-line grade sheet is available during the semester that contains scores for all graded assignments and exams. Oral communications scores are also included. Grades are updated frequently so that students know their up-to-date class status. The grade sheet also contains a ranking so that students know their ranking in the class according to the grading formula during the semester. All graded reviews (e.g., code reviews) include frequent feedback during the review. Following the session, the comments are summarized and available to the students on request.

Lectures and Assignments

We will be following the syllabus closely. The assigned reading for the class will be found in chapters of the textbooks and in documents (articles, standards, etc.) available on the Internet. The readings are included in the class notes and in a page on the class Web site. A summary of the topics covered in the course are shown in the class session calendar below. There might be some variations in the scope of the topics and the dates of various topics based on rate of progress of the class.

Click on the lecture topic below to download a PDF file containing the class notes.

Date Topics
1/27 (Tu) Introduction
1/29 Python Setup
2/3 (Tu) Course background
2/5 Course background (continued)
2/10 (Tu) Political contributions (and DataFrames)
2/12 Political contributions (and DataFrames) - continued
2/17 (Tu) Political contributions (and DataFrames) - continued
2/19 Quiz preparation, Python/Pandas debugging
2/24 (Tu) Snow closing
2/26 Quiz, Election process data
3/3 (Tu) Voter registration
3/5 Voter registration (continued)
3/10 (Tu) Geographic data display
3/12 Geographic data display (continued)
3/17 (Tu) Spring Break - no class
3/19 Spring Break - no class
3/24 GeoJSON
3/26 Midterm exam
3/31 (Tu) Map integration
4/2 (Th) Map integration (continued)
4/7 (Tu) Quiz, Election results data
4/9
Redistricting
4/14 (Tu) Gerrymandering
4/16 Voting Rights Act
4/21 (Tu) VRA (continued)
4/23 Quiz, Social Media
4/28 (Tu) Social media data analysis
4/30 VRA Revisited
5/5 (Tu) Social Media (continued)
5/7 (Th) Case study - 2016 election
5/14 (Th) 11:30AM-12:30PM Final Exam

Development Tools

To complete the homework assignments, you will need to either use the Stony Brook University Lab facilities (Computer Science Labs and Synch Sites) and/or install the required software on your computer. The following software is required:

Assignment Information

You are expected to work on the project as part of a small group (maximum of 3 students in a group).

Every week you will be assigned reading. There will also be 5-7 assignments during the semester.
On-time submission of the assignments will count as the assignment portion of your grade. The material in the programming assignments constitutes a large component of the mid-term and final exams.
When you submit an assignment, please include the following in the body of the e-mail.

Grades and Exams

This is a three-credit graded course. Your final grade is based primarily on your exam and quiz scores (mid-term and final exams, along with 2-5 quizzes). Assignments will be graded on a range of 0-10, and the total of all the assignments will constitute your assignment grade. Any late assignments will be accepted up to 2 days after the due date, but there will be a 2-point penalty for any late submission. Assignment and quiz grades will be normalized so the final grade in each category will be in the range 0-100. There will also be an oral communications score, which is determined by the quality of in-class interactions. The weighting of the midterm exam, the final exam, the quizzes, HW assignments, and oral communications is 35/30/15/10/10. The weighting of grade components will be used to determine the ranking of each student in the class. Final grades will be assigned based on the ranking, with a grade distribution reasonably consistent with similar courses.

Extra points may be added to your exam scores for correct answers to certain in-class questions during regular class meetings. We will also have in-class hands-on programming exercises. You can work on these exercises in a small group (sharing a computer), and the first group to complete the exercise may receive extra credit in the subsequent exam. 
All the exams will be closed book. However, portions of relevant class libraries and APIs will be provided to you, if necessary. The exams will be composed of some short answer questions and some programming questions. For the programming questions, your understanding of the concepts will be more important than your knowledge of the exact syntax.
Be sure to bring your student ID to all exams. The TAs will check your ID, and no one will be allowed to take an exam without the proper ID. 

Be sure to be in class on-time for you assigned examination time since there will be no make-up exams. However, students participating in University-sponsored activities will be offered options for make-up of exams and assignments consistent with the University policy as stated in the Undergraduate Bulletin. Similarly, accommodations to students concerning syllabus assignment and exam policies for religious reasons will be granted consistent with Undergraduate Bulletin policies.
The Pass/No Credit (P/NC) option is not available for this course.
The class includes some hands-on programming, so you will require access to a computer and a development environment. The class-standard development environment is included in computers in the Computer Science Labs. If you need to quickly set up an account, please contact the Computer Science (CS) Department system staff. You will need to provide the CS Systems staff with your student ID and an e-mail address. An e-mail will be sent to you when the account is ready.

The Pass/No Credit (P/NC) option is not available for this course.

Academic Integrity & Behavior

Each student must pursue his or her academic goals honestly and be personally accountable for all submitted work. Representing another person's work as your own is always wrong. Faculty is required to report any suspected instances of academic dishonesty to the Academic Judiciary. For more comprehensive information on academic integrity, including categories of academic dishonesty please refer to the Academic Integrity.

Students are expected to attend every class, report for examinations and submit major graded coursework as scheduled. If a student is unable to attend lecture(s), report for any exams or complete major graded coursework as scheduled due to extenuating circumstances, the student must contact the instructor as soon as possible.  Students may be requested to provide documentation to support their absence and/or may be referred to the Student Support Team for assistance. Students will be provided reasonable accommodations for missed exams, assignments or projects due to significant illness, tragedy or other personal emergencies. In the instance of missed lectures or labs, the student is responsible for review posted slides, participation in Piazza interaction, and seeking additional information from classmates, TAs, ad the instructor.  Please note, all students must follow Stony Brook, local, state and Centers for Disease Control and Prevention (CDC) guidelines to reduce the risk of transmission of COVID.

Special Assistance

If you have a physical, psychological, medical or learning disability that may impact your course work, please contact Student Accessibility Support Center, Stony Brook Union Suite 107, (631) 632-6748 or at sasc@stonybrook.edu . They will determine with you what accommodations, if any, are necessary and appropriate. All information and documentation is confidential.

Students who require assistance during emergency evacuation are encouraged to discuss their needs with their professors and Student Accessibility Support Center. For procedures and information go to the following website: http://www.stonybrook.edu/ehs/fire/disabilities.

Stony Brook University expects students to respect the rights, privileges, and property of other people. Faculty are required to report to the Office of University Community Standards any disruptive behavior that interrupts their ability to teach, compromises the safety of the learning environment, or inhibits students' ability to learn. Faculty in the HSC Schools and the School of Medicine are required to follow their school-specific procedures. Further information about most academic matters can be found in the Undergraduate Bulletin, the Undergraduate Class Schedule, and the Faculty-Employee Handbook.

Reading

  1. Carson & Jacobson, Chapter 2