Ontology learning is the process of utilizing machine learning techniques to automatically construct ontologies. Automated
ontology learning is a complex task that requires many different systems in order to effectively learn ontologies. One critical
aspect of ontology learning is word sense disambiguation (WSD). WSD is the process of determining the correct definition
of an ambiguous term. Many approaches to WSD have been proposed; however, few have taken advantage of the power of
social media. In this paper, a new approach to WSD was proposed and a prototype developed to automatically disambiguate
words from twitter. We have provided preliminary evidence that social media can be a valuable tool to aid in word sense
disambiguation and in turn ontology learning. Our future research includes conducting a large-scaled evaluation of the
proposed method for WSD. Additionally, we will determine the sensitivity of the performance of WSD to the size of social
media context. Further, development and testing of a full-fledged ontology learning system as well as assessing the impact of
WSD on the effectiveness of ontology learning will be performed