Subjectivity Mining

2019-2020

Course Objective

Understanding subjectivity in text by analyzing opinions, sentiment,
modality, speculation, etc. Annotating layers of subjectivity in tekst;
Developing and using subjectivity lexicons; Design a research
environment where NLP techniques are used to solve a subjectivity mining
subtask (such as sentiment analysis, stance detection, hate speech
detection, etc.). Interprete and analyze results of the subjectivity
mining
process.

Course Content

Subjectivity is one of the key elements of natural language. Every
communicative act is subjective to some degree. Subjectivity starts with
the intentions of the producer of the message and affects its associated
functions and syntactic structures, not to mention the choice of
vocabulary and associated connotations. This course combines theoretical
linguistic notions used in techniques such as sentiment analysis and
opinion mining with hands-on work on real
language data. Moving between theory, discussions, practical
data annotation and tools (e.g. sentiment analysis, opinion mining) you
explore some of the following linguistic
phenomena:
modality, sentiment, emotions, opinions and stance.

Teaching Methods

lectures (2 hours/2 times per week)

Method of Assessment

Weekly assignments and course paper

Literature

to be announced

Target Audience

Students of the Research Master's Humanities, in particular Linguistics
(Human Language Technology) and master-students of Artificial
Intelligence and Computer science.

Recommended background knowledge

Basic Linguistic knowledge and programming skills (Python)

General Information

Course Code L_AAMPLIN018
Credits 6 EC
Period P1
Course Level 500
Language of Tuition English
Faculty Faculty of Humanities
Course Coordinator dr. E. Maks
Examiner dr. E. Maks
Teaching Staff dr. E. Maks

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Seminar
Target audiences

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