This study focus on the contrasting dynamics of discussion and information dissemination on two influential platforms: Twitter and Wikipedia. While Twitter often serves as a battleground for contentious debates, where users engage in direct confrontation, Wikipedia fosters a collaborative environment aimed at reaching consensus. Focusing on polarizing issues such as the ongoing Russian invasion of Ukraine, the research examines how information is shared, contested, and shaped within these distinct communities. Data from Twitter, collected using the hashtag #UkraineRussiaWar, undergoes a NLP process to categorize and highlight the diverse topics discussed. By classifying the data into Pro-war or Against-war perspectives, we analyze user reactions and the primary themes driving these discussions. For Wikipedia, we gathered and analyzed comments and contributions from various authors, providing insights into the collaborative discourse and consensus-building process.