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Sentimental Roadmap: Labeling a Dataset for Targeted Analysis

T. Aditya Sai Srinivas, B. Thulasi Thanmai, A. David Donald, G. Thippanna, I. V. Dwaraka Srihith

Abstract


Preparing datasets for data science tasks is a time-consuming process, often involving data cleaning and labeling. Labeling unlabeled data is particularly crucial, and one significant application where it plays a vital role is sentiment analysis. Sentiment analysis involves analyzing user reviews and comments to determine sentiment, making it essential to add labels to the dataset before analysis. This article offers a comprehensive tutorial on effectively labeling unlabeled data for sentiment analysis using Python. By following this tutorial, data scientists can gain valuable insights into the process of adding labels, enabling them to unlock the power of sentiment analysis for various applications.

 


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References


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