Michal Ptaszynski

AAAI Conference 2010 Conference Paper

CAO: A Fully Automatic Emoticon Analysis System

• Michal Ptaszynski
• Jacek Maciejewski
• Pawel Dybala
• Rafal Rzepka
• Kenji Araki

This paper presents CAO, a system for affect analysis of emoticons. Emoticons are strings of symbols widely used in text-based online communication to convey emotions. It extracts emoticons from input and determines specific emotions they express. Firstly, by matching the extracted emoticons to a raw emoticon database, containing over ten thousand emoticon samples extracted from the Web and annotated automatically. The emoticons for which emotion types could not be determined using only this database, are automatically divided into semantic areas representing "mouths" or "eyes", based on the theory of kinesics. The areas are automatically annotated according to their co-occurrence in the database. The annotation is firstly based on the eyemouth-eye triplet, and if no such triplet is found, all semantic areas are estimated separately. This provides the system coverage exceeding 3 million possibilities. The evaluation, performed on both training and test sets, confirmed the system's capability to sufficiently detect and extract any emoticon, analyze its semantic structure and estimate the potential emotion types expressed. The system achieved nearly ideal scores, outperforming existing emoticon analysis systems.

AAMAS Conference 2010 Conference Paper

Multi-humoroid: Joking System That Reacts With Humor To Humans' Bad Moods

• Pawel Dybala
• Michal Ptaszynski
• Rafal Rzepka
• Kenji Araki

This paper contributes to the field of humoroids - humor-equipped conversational agents. We present our multi-agentsystem (multi-humoroid), which tells jokes according to users'emotions, in order to make them feel better. We briefly describethe components and the design of the system, and present resultsof two experiments showing that the system with humor wasevaluated as generally better than a baseline dialogue agent.

IJCAI Conference 2009 Conference Paper

• Michal Ptaszynski
• Pawel Dybala
• Wenhan Shi
• Rafal Rzepka
• Kenji Araki

This paper presents a novel approach to the estimation of user’s affective states in Human-Computer Interaction. Most of the present approaches divide emotions strictly between positive or negative. However, recent discoveries in the field of Emotional Intelligence show that emotions should be rather perceived as context-sensitive engagements with the world. This leads to a need to specify whether the emotions conveyed in a conversation are appropriate for a situation they are expressed in. In the proposed method we use a system for affect analysis on textual input to recognize users emotions and a Web mining technique to verify the contextual appropriateness of those emotions. On this basis a conversational agent can choose to either sympathize with the user or help them manage their emotions. Finally, the results of evaluation of the proposed method with two different conversational agents are discussed, and perspectives for further development of the method are proposed.