Twitter, a popular social networking platform, provides a medium for people to share information and opinions with their followers. In such a medium, a flash event finds an immediate response. However, one concept may be expressed in many different ways. Because of users' different writing conventions, acronym usages, language differences, and spelling mistakes, there may be variations in the content of postings even if they are about the same event. Analyzing semantic relationships and

more »

... g these variations have several use cases, such as event detection, and making recommendations to users while they are posting tweets. In this work, we apply semantic relationship analysis methods based on term co-occurrences in tweets, and evaluate their effect on detection of daily events from Twitter. The results indicate higher accuracy in clustering, earlier event detection and more refined event clusters.