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TextBlob VS MeaningCloud

Compare TextBlob VS MeaningCloud and see what are their differences

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TextBlob logo TextBlob

Natural Language Processing (NLP)

MeaningCloud logo MeaningCloud

Extract meaning from unstructured text and turn it into actionable insights.
  • TextBlob Landing page
    Landing page //
    2020-03-01
  • MeaningCloud Landing page
    Landing page //
    2022-07-28

TextBlob features and specs

  • Ease of Use
    TextBlob is designed with simplicity in mind, offering an easy-to-use interface for processing text data, making it accessible for both beginners and experienced developers.
  • Linguistic Features
    It provides a range of natural language processing tasks such as noun phrase extraction, sentiment analysis, and part-of-speech tagging, which are built-in and readily available with simple commands.
  • Integration Capabilities
    TextBlob integrates seamlessly with other libraries such as NLTK and Pattern, allowing for enhanced functionality and extended features.
  • Pre-trained Models
    The library includes pre-trained models for various languages, enabling quick start without the need for extensive training or configuration from scratch.

Possible disadvantages of TextBlob

  • Performance Limitations
    While suitable for small to medium-sized projects, TextBlob may not perform optimally with very large datasets, potentially leading to slower processing times compared to more robust NLP frameworks.
  • Limited Deep Learning Features
    TextBlob doesn't support the latest deep learning-based NLP advancements like those available in libraries such as SpaCy or Hugging Face's Transformers.
  • Language Support
    Although TextBlob supports multiple languages, its accuracy and feature set are primarily optimized for the English language, with varying results for other languages.

MeaningCloud features and specs

No features have been listed yet.

TextBlob videos

+ Add

Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python

More videos:

  • Tutorial - How to Calculate Sentiment Using TextBlob - Part 5 - Python Yelp Sentiment Analysis
  • Review - A Quick Guide To Sentiment Analysis | Sentiment Analysis In Python Using Textblob | Edureka

MeaningCloud videos

+ Add

When to Use the Different Text Analytics Tools - MeaningCloud

More videos:

  • Review - Topic Extraction with MeaningCloud and Graphileon
  • Review - MeaningCloud Signup and Office 365

Category Popularity

0-100% (relative to TextBlob and MeaningCloud)

TextBlob

MeaningCloud

Spreadsheets
74 74%
Spreadsheets
26% 26
Natural Language Processing
63 63%
Natural Language Processing
37% 37
NLP And Text Analytics
70 70%
NLP And Text Analytics
30% 30
Analytics
0 0%
Analytics
100% 100

User comments

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What are some alternatives?

When comparing TextBlob and MeaningCloud, you can also consider the following products

spaCy - spaCy is a library for advanced natural language processing in Python and Cython.

BytesView - BytesView data analysis tool is one of the most effective and easiest ways to extract insights for unstructured text data.

Amazon Comprehend - Discover insights and relationships in text

Medallia - Medallia enables companies to capture customer feedback, understand it in real-time, and take action to improve the customer experience (CX).

OpenNLP - Apache OpenNLP is a machine learning based toolkit for the processing of natural language text.

Talkwalker - Talkwalker Consumer Intelligence Platform: built for speed of insight, ease of use, and data democratization

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