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The baseline supervised learning techniques such as SVM, etc., have been firstly implemented with the traditional tf-idf model and then with the novel feature optimization model. Benchmark Kaggle dataset, which includes a collection of tweets is considered to report the results. The results are assessed on the basis of performance accuracy. Empirical analysis validates that the proposed implementation of a binary cuckoo search for feature selection optimization in a sentiment analysis task outperforms the elementary supervised algorithms based on the conventional tf-idf score.<\/p>","DOI":"10.4018\/ijirr.2019010101","type":"journal-article","created":{"date-parts":[[2018,10,31]],"date-time":"2018-10-31T12:41:18Z","timestamp":1540989678000},"page":"1-15","source":"Crossref","is-referenced-by-count":15,"title":["Sentiment Analysis Using Cuckoo Search for Optimized Feature Selection on Kaggle Tweets"],"prefix":"10.4018","volume":"9","author":[{"given":"Akshi","family":"Kumar","sequence":"first","affiliation":[{"name":"Delhi Technological University, Delhi, India"}]},{"given":"Arunima","family":"Jaiswal","sequence":"additional","affiliation":[{"name":"Indira Gandhi Delhi Technical University for Women, Delhi, India"}]},{"given":"Shikhar","family":"Garg","sequence":"additional","affiliation":[{"name":"Delhi Technological University, Delhi, India"}]},{"given":"Shobhit","family":"Verma","sequence":"additional","affiliation":[{"name":"Delhi Technological University, Delhi, India"}]},{"given":"Siddhant","family":"Kumar","sequence":"additional","affiliation":[{"name":"Delhi Technological University, Delhi, India"}]}],"member":"2432","reference":[{"key":"IJIRR.2019010101-0","doi-asserted-by":"crossref","unstructured":"Kumar, A., & Sharma, A. 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