Computer Science E6998:
Computational Models of Social Meaning
Spring 2015
[Announcements] [General Information]

  • April 23: Class on April 30th starts at 4pm instead of 4:10 to accomodate all presentations!!
  • April 16: Updated due date for Project Final Paper. Now due May 8, 11:59pm. One final paper per team uploaded on CourseWorks
  • March 12: Updated due date for Project Literature Rview. Now due April 2
  • Feb 18: Readings list was updated to include suggested general readings for the Belief and Hedge Analysis lecture
  • Feb 5: Final list of papers for discussion and assignment of discussant for each article
  • Jan 27: Full list of readings for the semester is up. They are in the table below. Each week we will discuss readings introduced in the previous week. Please choose your top 5 papers and upload an Excel document with your name on first column and your 5 top choices in the next 5 consecutive columns When selecting the papers please do not use full citation, use just the label assigned next to each reading: e.g. [SL1], [BH3], [BH1]. A template is given here: Template File . Example of record filling:
    Smaranda Muresan     [SL1]     [BH3]     [BH1]     [SI1]    [P1]
    (where [SL1] is your top choice, [BH3] is your second choice and so on

    Please save the file with PaperDiscussionYourLastName and upload on Dropbox on CourseWorks no later than January 29 9:00am. We will try to keep track of your preferences as much as possible.

  • Welcome to Computational Models of Social Meaning!

General Information


Computatioal Models of Social Meaning is a seminar in Natural Language Processing, focusing on computational methods for extracting social and interactional meaning, mainly from conversational text (and speech). Topics include detection of speaker's sentiments, emotions, opinions and beliefs, sarcasm, deception, persuation, perspective, power and influence, politeness, and personality. Analysis of meaning-bearing characteristics of the speaker and topic, including text, discourse, prosodic and other cues.


  • COMS 3133/4/7/9 (Data Structures) or equivalent programming ability in at least one systems or scripting language (C++, Java, Python)

Instructor: Smaranda Muresan

  • smara [who is at] ccls [dot] columbia [dot] edu
  • Office Hours: Thursdays 3:00pm-4:00pm
    Office: Center for Computational Learning System, Interchurch Center (Room 850)


  • Email: TBD
  • Office Hours: TBD


  • Thursday 4:10-6:00, MUD 644
The class consists of lectures and discussion of research papers led by students. To facilitate the discussion of research articles on a particular topic each week, the topic is introduced the previous week. Thus, the class structure will be as follows: lecture on new topic and discuss of papers on topic introduced in the previous week.

Grade Breakdown

  • 10% Data Analysis Assignments

  • There will be 3 data analysis assignments that will require relatively small amount of work to learn about a data source. You will be asked to answer one or two questions and to notice some interesting points about the data source. The grading for this will be Excellent/Good/Insufficient. The data analysis assignments will be due before class, on Courseworks site. Late assignments will not be accepted, except emergency situations.

  • 30% Discussion of Papers

  • Each student will do a critical discussion of ONE of the research articles proposed for reading. Students will prepare a brief presentation of the paper (Input? Output? What does it do? How is evaluated? How does it relate to other work in the field) followed by leading a critical discussion on key positive and negative aspects, availability of code and datasets. You can consider as inspiration guidelines given to reviewers of conference papers Review Form ). But all the time explain your ratings.

    NOTE: Every week every student needs to write a short paragraph about each of the papers given for discussion (there will be 2-3 papers), and write what you liked and what you did not like about the paper (can be one positive aspect and one negative). This will allow a good discussion in class. These summaries are not graded BUT they are REQUIRED. Missing a significant number of these write-up will result in a lower grade!!

  • 60% Final Project

  • Design and implement a software product of appropriate scope and complexity given the time constraints. Project should be related to one topic discussed in class or related issues. Prepare a literature review (by mid semester), give a class presentation and a paper write-up describing the methodology and results. Groups of 2-3 are welcome as is individual work (complexity expectations being tuned accordingly). Split up of grades will be 10% for literature review, 5% class presentations, 45% for project and final paper.


Schedule is tentative and highly subject to change.

Date Topics Readings Handouts & Due dates
1/22 Class Introduction
1/29 Sentiment Analysis: Sentiment Lexicons General reading for lecture
2/5 Sentiment Analysis Discussion papers on Sentiment Lexicons: Data Analysis Assignment 1 Out
2/12 Emotion/Mood Detection Discussion papers on Sentiment Analysis: Data Analysis Assignment 1 due
2/19 Belief Analysis and Hedging Suggested General Readings relevant to guest lecture:

Discussion papers on Emotion/Mood Detection:

Project: Project ideas due Feb 17, 11:59pm (note unusual time)
2/26 Irony and Sarcasm Detection Discussion papers on Belief Analysis and Hedging:
3/5 Agreement/Disagreement Discussion papers on Sarcasm/Irony Detection: Project Proposal due
3/12 Perspective/Ideology Discussion Papers on Agreement/Disagreement:
3/19 No Lecture: Spring Break
3/26 Social Power Discussion Papers on Perspective/Ideology:
4/2 Deception Discussion Papers on Social Power: Project: Literature Review Due
4/9 Extracting Social Networks Discussion Papers on Deception:
4/16 Personality and Interpersonal Stance Discussion Papers on Extracting Social Networks:
4/23 TBD Discussion Papers on Personality and Interpersonal Stance:
4/30 Final Project Presentations (start time 4:00pm) Project: Presentations due;
Project: Final paper due May 8 11:59pm

smara [who is at] ccls [dot] columbia [dot] edu

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