Social media posts and their comments are rich in variation of subjects and an interesting pool for opinion mining. Individuals engage in social communications on Facebook through three behaviors: like, share and comment on a Facebook post. Responses to comments are grouped under the respective comment as a conversation thread. Conversation threads become interesting when users have conflicting views with the article posted, or with the opinion of another user. Our research goal is to answer questions such as why some posts in Facebook receive more attention than others? Are conversation threads following a similar pattern between subjects like sport and politics? Is there any harmony between conversation threads of different subjects? We investigated how individuals react to different conversation subjects in the Facebook through a comprehensive analysis. Our aim is to discover semantic and sentimental patterns in conversation threads categories. Finally, we employed Natural Language Processing techniques such as semantic and sentimental analysis and statistical methods like average response time (ART) and average comment length (ACL) of a post and observed that there are interesting patterns exists among different conversation threads.