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The sentiment of reviews is binary (1 for postive, 0 for negative).\n\nThis source dataset was collected in association with the following publication:\n\n```Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). \"Learning Word Vectors for Sentiment Analysis.\" The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011).```\n\n### Usage\n- Install the required tools \n\n    ```pip install -r requirements.txt```\n- Run the script \n    \n     ```python text_classifier.py```\n\n### References\n- Kaggle – Bag of Words Meets Bags of Popcorn (https://www.kaggle.com/c/word2vec-nlp-tutorial)\n- Gensim – Deep learning with paragraph2vec (https://radimrehurek.com/gensim/models/doc2vec.html)\n- Quoc Le and Tomas Mikolov. Distributed Representations of Sentences and Documents (https://arxiv.org/pdf/1405.4053v2.pdf)\n","funding_links":[],"categories":["Python"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fibrahimsharaf%2Fdoc2vec","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fibrahimsharaf%2Fdoc2vec","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fibrahimsharaf%2Fdoc2vec/lists"}