More and more of life is now manifested online, and many of the digital traces that are left by human activity are increasingly recorded in natural-language format. This research-oriented course examines the opportunities for natural language processing to contribute to the analysis and facilitation of socially embedded processes. Possible topics include analysis of online conversations, learning social-network structure, analysis of text in political or legal domains, review aggregation systems. CDNM's web page CDNM's web page

Prerequisites, enrollment, related classes

Prerequisites All of the following: CS 2110 or equivalent programming experience (Python encouraged); a course in artificial intelligence or any relevant subfield (e.g., NLP, information retrieval, machine learning, Cornell CS courses numbered 47xx or 67xx); proficiency with using machine learning tools (e.g., fluency at training an SVM, comfort with assessing a classifier’s performance using cross-validation)

Enrollment Limited to [[PhD and [CS MS] students] who meet the prerequisites]. If you are interested in taking the class but do not belong to these categories, come to first day of class when enrolment will be discussed. Auditing (either officially or unofficially) is not permitted.

Related classes: see Cornell's NLP course list

The homepage for the previous running of CS6742 may also be useful. Here is the list of all prior runnings: 2017 fall :: 2016 fall :: 2015 fall :: 2014 fall :: 2013 fall :: 2011 spring

Administrative info and overall course structure

Course homepage Main site for course info, assignments, readings, lecture references, etc.; updated frequently.

CMS page Site for submitting assignments, unless otherwise noted.

Piazza page Course announcements and Q&A/discussion site. Social interaction and all that, you know. (Access code provided on first day of classes.)

Contacting the instructor

Overview of course schedule. Details subject to change. Full schedule is maintained on the main course webpage.

Lecture Agenda Pedagogical purpose Assignments

Course overview


Pilot empirical study for a research idea based on readings provided.

# 2 - #3

Get-to-know-you exercises to get everyone familiar and comfortable with each other. A1 related discussions.

How to form research questions and quickly test their feasibility.  
# 4 - #7

Lecture topics related to the A1 readings: Online reviews: individual expression, community dynamics; Online asynchronous conversations.

Case studies to explore some topics and research styles find interesting.

Next block of meetings

Lectures on, potentially, linguistic coordination, linguistic adaptation, influence, persuasion, diffusion, discourse structure, advanced language modeling

Foundational material

Potentially some assignments based on the lectures.

Next block of meetings

Dicussion of proposed projects based on the readings

Practice with fast research-idea generation. Feedback as to what proposals are most interesting, most feasible, etc.

Discussion of student project proposals, based on the readings for that class meeting. Each class meeting thus involves everyone reading at least one of the two assigned papers and posting a new research proposal based on the reading to Piazza.

Thoughtfulness and creativity are most important to , but take feasibility into account.

Remainder of the course

Activities related to course projects

Development of a "full-blown" research project (although time restrictions may limit ambitions). For our purposes, "interesting" is more important than "thorough".


Some time in December (to be determined by the registrar): final project writeup due

Grading Of most interest to is productive research-oriented discussion participation (in class and on Piazza), interesting research proposals and pilot studies, and a good-faith final research project.

Academic Integrity Academic and scientific integrity compels one to properly attribute to others any work, ideas, or phrasing that one did not create oneself. To do otherwise is fraud.

We emphasize certain points here. In this class, talking to and helping others is strongly encouraged. You may also, with attribution, use the code from other sources. The easiest rule of thumb is, acknowledge the work and contributions and ideas and words and wordings of others. Do not copy or slightly reword portions of papers, Wikipedia articles, textbooks, other students' work, Stack Overflow answers, something you heard from a talk or a conversation or saw on the Internet, or anything else, really, without acknowledging your sources. See and for more information and useful examples.

This is not to say that you can receive course credit for work that is not your own — e.g., taking someone else's report and putting your name at the top, next to the other person(s)' names. However, violations of academic integrity (e.g., fraud) undergo the academic-integrity hearing process on top of any grade penalties imposed, whereas not following the rules of the assignment only risk grade penalties.




Note that assignments will remain visible even when details are hidden.
#1 Aug 29: Course overview: scope, course goals, course design
  • Details will be appear here before each lecture.
  • Assignment A1 released (updates on Piazza)
  • Student-information assignment released on Piazza

Class images, links and handouts



#2 Sep 3: From monologues to conversations

Class images, links and handouts

#3 Sep 5: Discussion of A1. Types and properties of conversations

Class images, links and handouts

  • Gonzalez-Bailon, Sandra, Andreas Kaltenbrunner, and Rafael E. Banchs. 2010. The structure of political discussion networks: A model for the analysis of online deliberation. Journal of Information Technology 25(2): 230-243. [ author-posted version]
  • #4 Sep 10: Conversational structure

    Class images, links and handouts

    #5 Sep 12: Conversatinal language. Case study: from hypothesis to research (Coordination)
    Class images, links and handouts


  • Danescu-Niculescu-Mizil, Cristian and Lillian Lee. 2011. Chameleons in imagined conversations: A new approach to understanding coordination of linguistic style in dialogs. Proceedings of the ACL Workshop on Cognitive Modeling and Computational Linguistics.
  • Daniel M. Romero, Roderick I. Swaab, Brian Uzzi, Adam D. Galinsky. 2015. Mimicry Is Presidential: Linguistic Style Matching in Presidential Debates and Improved Polling Numbers
  • Tim Althoff, Kevin Clark, Jure Leskovec. 2016 Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health TACL.

  • Code for generating the calendar formatting adapted from the original versions created by Andrew Myers