Text Mining and Analysis in R
Instruction: Describe the process of conducting text mining in R, including data import, cleaning, and sentiment analysis.
Context: This question evaluates the candidate's familiarity with text mining techniques in R, useful for extracting insights from unstructured text data.
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Keep one record per document with a stable ID, original text, language, source and collection time. Import with an explicit encoding and data-use permission; preserve raw text before normalization.
Choose tokenization and cleaning for the task. Removing punctuation, numbers or stop words can destroy sentiment, negation, product codes or meaningful units. HTML should be parsed appropriately, and any language-specific normalization should be recorded...