Tree-Based Mining with Sentiment Analysis for Discovering Patterns of Human Interaction in Meetings

Human interaction is one of the most important characteristics of group social dynamics in meetings. The sequence of human interaction is generally represented as a tree. Tree structure is used to capture how the person interacts in meetings and to discover the interactions. The human interaction are proposing as an idea, giving comments, ask opinion, acknowledge, etc., Frequent interaction tree pattern mining algorithm and Frequent interaction sub tree pattern mining algorithm are utilized to analysis the structure and to extract interaction flow patterns, where co-occurring only the tags are considered. To overcome this problem, Sentiment Analysis (SA) is proposed work to the entire flow of interaction in meetings. A sentiment analysis approach to extract sentiments associated with opinions of positive or negative for specific subjects the from the document instead of classifying the whole document into positive or negative. Sentiment analysis approach identifies the semantic relationship between the sentiment expressions and subject properly and also improve the performance of discovering pattern of Human interactions in meetings.