Opinion Mining is becoming the fastest growing area to extract useful and insightful information to support decision making. In the age of social media, user’s opinions and discussions have become a highly valuable source to look for users preferences, likes, and dislikes. The industry of wildlife parks (or zoos) is a competitive domain that requires careful analysis of visitor’s opinions to understand and cater for their preferences when it comes to wildlife. In this thesis, an opinion mining approach was proposed and applied on textual posts on the social media platform, Twitter, to extract the popularity, polarity (sentiment), and emotions toward birds and bird types such as owls, sparrows, etc. Then, the thesis provides recommendations based on popularity of birds and bird types and a ranked list of the most desired birds based on consumer emotions toward them. The findings of this thesis can help wildlife parks in the decision-making process on the types of birds to acquire.