Social media has become an important communication tool especially following an extreme event. Research in social psychology has shown that people engage in gathering and 'milling' information, and confirmation seeking during the process of forming intent to take action or voice an opinion. Twitter serves as a communications channel where people converge to compile collective intelligence, provide event reporting, and diffuse information. In this paper the investigation of Twitter usage seeks to describe human participation on Twitter following a controversial extreme event-2013 Syria sarin gas attack. The methodology employed incorporates Natural Language Processing (NLP) and network analysis to trace human response on Twitter to this event. NLP techniques include Named Entity Recognition (NER) used to extract relevant entities (e.g. countries), Event Extraction (EE) to excerpt relevant events (e.g. conflict, movement, life, etc.), and Stanford Parser to detect actionable verbs discussed by Twitter participants. Network analysis constructs a network based on the Twitter users' communications, detects communities, extracts their leaders and identifies their roles based on structural properties of the networks. Specifically, the research looked at the Twitter data for two days August 22-23, 2013 following the event. The research suggests that (1) there were no immediate polarization of opinions following the event, (2) the primary event of Twitter communication was the conflict and information about the victims of the event, (3) Twitter communities were too sparse to produce substantial amount of social pressure to force an opinion/opinion shift, (4) top community leaders were news sources, political activists, and select individuals, (5) 'individual' leaders political agendas were not revealed.