This study provides insight about how voluntary organizations active in disaster communicate via posts on Twitter as extending social solidarity through their disaster relief efforts. With tweets from Twitter accounts associated with member organizations from two associations, the National Voluntary Organizations Active in Disaster and the Louisiana Voluntary Organizations Active in Disaster, the research examines social cohesion and civil society through thematic topics which emerge from the organizations’ tweets posted during the four months following the August 2016 Louisiana floods. With the text mining methodology of topic modeling, I identify, compare, and contrast latent topics that exist among the organizations’ Twitter user timelines. Topic modeling provides a relational method for discovering topics by calculating and learning statistical associations between words within a series of documents such as organizations’ tweets. The voluntary organizations use social media as a tool for interacting with their publics and maintaining a visible online presence. Through focusing on their use of Twitter, the research examines how organizations use a social media platform like Twitter to socially construct moral and social dimensions of disaster relief to engage the public with civil society.