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2022-08-22

Top Python Libraries for Sentiment Analysis

Top Python Libraries for Sentiment Analysis
  1. NLTK (Natural Language Toolkit): A powerful library for natural language processing in Python, providing a wide range of tools for text processing and computational linguistics, including a module for sentiment analysis.
  2. TextBlob: A library for common text-processing tasks in Python, including part-of-speech tagging, noun phrase extraction, sentiment analysis, and more.
  3. spaCy: An open-source library for advanced natural language processing in Python, providing fast and accurate syntactic and semantic analysis, it also includes a sentiment analysis library.
  4. VADER (Valence Aware Dictionary and sEntiment Reasoner): A lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media.
  5. Pattern: A web mining module for the Python programming language, that provides web services for several natural language processing tasks, including sentiment analysis.
  6. gensim: A library for topic modeling and document similarity analysis in Python, built on top of NumPy and SciPy, it also includes a sentiment analysis library.
  7. StanfordNLP: A python wrapper for Stanford CoreNLP (Java Library) which provides several natural language processing tools such as part-of-speech tagging, named entity recognition, and sentiment analysis.
  8. PyNLPI: A library for natural language processing in Python, providing a wide range of tools for text processing, including sentiment analysis.
  9. Flair: A library for state-of-the-art natural language processing in Python, providing simple and efficient tools for