SENTAL
Sentiment Analysis for User Generated Discourse in eLearning 2.0
Motivation
One prominent feature of eLearning 2.0 is collaboration. Members interact, learn
and share their opinions by creating mass amount of discourse through wikis, blogs and
forums. However, this growing amount of user generated discourse places considerable
burdens on learners as well as instructors who wish to track learners' opinions and views
on diverse topics or search for content containing opinions.
Goals
Enabling subjectivity and sentiment analysis for generating feedback from user generated discourse and for supporting information search in eLearning 2.0:
- investigate knowledge- and corpus-based methods for subjectivity and sentiment analysis
- determine the semantic orientation and strength of the opinions
- identify the targets of the opinions
- identify the holders of the opinions
System Architecture

Data
Darmstadt Service Review Corpus
People
- Prof. Iryna Gurevych, Principal Investigator
- Dipl.-Inf. Cigdem Toprak, Doctoral Researcher