Complete this form if you want to enroll in the class.
For your reference, the course description, prerequisites and learning objectives are below:
Wednesdays 2:00pm - 4:30pm in Upson Hall 102
Description: As conversations become central to the way in which we acquire and consume information
and as the societal implications became evident (e.g., the potential for misinformation, hate
speech, ethical questions surrounding the use of chatbots), there is an increasing need for
automated ways to analyze their quality. This course will cover computational approaches to
conversational analysis: starting from topics that were traditionally addressed within the
Sociology subfield of Conversational Analysis, continuing with reviewing existing computational
methods that address those topics, and further guiding the development of new methods and
their application to real-life conversational data. In addition to lecturing in-class activities will
include close interaction with conversational data, such as collaborative annotation of
conversational phenomena, in-depth discussion of hand-picked examples, as well as joint and
iterative development of annotation guidelines that lend themselves to computational
modeling.
Conversational phenomena will include: Politeness, Turn-taking, Coordination, Acculturation Misunderstandings and Repair.
Conversational domains will include: political discussions, online debates, mental health counseling.
Prerequisites, in addition to instructor permission.
1) Strong performance in INFO/CS 4300 or CS 4740 or another NLP course;
2) Programming proficiency: CS 2110 or equivalent with strong Python skills.
A) The students will be able to identify and characterize conversational phenomena;
B) The students will be able to analyze and annotate conversational data;
C) The students will be able to analyze conversations using computational techniques.
