Sentiment analysis also called as opinion mining is defined as the programmed learning of public's opinion, evaluations, and sentiment on different events, objects as well as their respective properties. Recently, it created high impact in academia and industry due to number of growing research problems and various applications. Selecting the features play a vital role in supreme data mining tasks since it assists in the reduction of data dimensionality by leaving the non-relevant features behind. Present work applies the ecological concept of habitat, ecological relationship and ecological succession for building an Ecology-Inspired Optimization algorithm named as Ecology Inspired Artificial Bee Colony algorithm (EI-ABC).Proposed method uses various population of candidate solution which cooperates and coevolves with one another, as per the given meta-heuristic algorithm. Sentiments are classified by using two classifiers viz., K Nearest Neighbor (KNN) and Classification and Regression Tree (CART). Result suggests that the EI-ABC algorithm proves to be interesting alternative for numerical optimization.
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