|Duration:||Two semesters (February – June 2015, February – June 2016)|
|Goals:||Investigate the effects of different linguistic modifiers on emotional expressions, and suggest how to model those effects within emotion recognition system.|
|Responsible TA:||Valentina Sintsova and Pearl Pu|
|Student Names:||Margarita Bolívar Jiménez (2015) and Nataniel Hofer (2016)|
|Keywords:||Emotion Recognition, Text Classification, Social Media Analysis, Modifiers Effects|
People express their emotions and feelings in multiple subtle ways. Even when they use explicit emotional terms, such as “happy” or “sad”, the emotional meaning of statements can change because of the variety of linguistic modifiers. Those include negation, intensity shifting, modality, and others. So far the researchers have investigated the effects of those modifiers on polarity of terms (positive vs. negative). However, their effects on more fine-grained emotion categories remain understudied. The first part of this project investigates the effects of different modifiers on emotional meaning of the terms via data analysis techniques. The second part studies to what extent the better modeling of modifiers improves emotion classification quality.