Profiling of Participants in Chat Conversations Using Creativity-Based Heuristics. Issue 1 (2nd January 2017) - Chiru, Costin-Gabriel; Rebedea, Traian
Abstract : This article proposes a new fully automated method for identifying creativity that is manifested in a divergent task. The task is represented by chat conversations in small groups, each group having to debate on the same topics, with the purpose of better understanding the discussed concepts. The chat conversations were created by undergraduate students in computer science studying human-computer interaction in several consecutive years. From this corpus of conversations, the chats from a single year were selected for analysis. These 25 chats contained 8, 798 utterance, made of 82, 176 word appearances with a vocabulary size of 5, 948 distinct words. By analyzing the resulted dataset of chat conversations, the creative ideas expressed by participants are automatically identified and extracted. The application is a first step in supporting creativity in online group discussions by highlighting the novel concepts present in conversations ( new ideas ) and also by identifying topics that could have become important, but they were forgotten during the debates ( lost ideas ). Once the ideas are identified, the system tries to also capture their developments, the reactions they attract and the conclusions that are drawn based on them. Because group constituency might influence the level of creative discourse within a conversation, the typology of each participant to the conversation is evaluated, starting from the analysis of the ideas already discovered, along with the utterances labeled as developments, reactions and conclusions.