EUROLAN 2007 Lecturers

- Rada Mihalcea and Carlo Strapparava -

Rada Mihalcea is an Assistant Professor of Computer Science at the University of North Texas.

Her research interests are in lexical semantics, multilingual natural language processing, and graph-based algorithms for text processing.

She is the president of the ACL Special Group on the Lexicon (SIGLEX) and a board member for the ACL Special Group on Natural Language Learning (SIGNLL). She was one of the coordinators of the Senseval-3 word sense disambiguation evaluation exercise.


Carlo Strapparava is a researcher at IRST, Trento, in the Natural Language Processing Group / Communication and Cognitive Technologies Division, since 1988.

His research activity covers artificial intelligence, natural language processing, intelligent interfaces, human-computer interaction, cognitive science, user models, adaptive hypermedia, lexical knowledge bases (WordNet/MultiWordNet), lexical semantics, word-sense disambiguation, and last but not least computational humor.

He is author of over a hundred of published papers, both in scientific journals and in conference proceedings.

- Tutorial: Words, Meanings and Emotions -

Slides

The affective analysis of text is an area of research that is becoming increasingly important, mostly because the detection and generation of emotions is a required component for many natural language processing applications (e.g., opinion mining, market analysis, affective computing, affective user-interfaces, e-learning environments, educational/edutainment games). This tutorial will focus on research issues relevant to how affective meanings are expressed in natural language, and it will introduce techniques for affective content detection and generation.

The following topics will be addressed:

  • Emotions in language, classification schemes for emotions
  • Affective lexical resources: WordNet Affect, SentiWordNet, ANEW, General Inquirer
  • Affective corpora: blogs and blog annotations
  • Emotion recognition in texts; problems and methodologies; direct and indirect affective words
  • Sentiment analysis; corpus-based and knowledge-based methods; bootstrapping
  • Affective categorization - some case studies:
    1. detecting happiness in blogposts;
    2. humorous one-liners
  • Humor; motivations for computational humor; humor generation and recognition
  • Dance with words: affective text animations.

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