Sentiment Analysis: VADER or TextBlob?

This article was published as a part of the Data Science Blogathon. What Is Sentiment Analysis? Conclusions are integral to practically all human exercises and are key influencers of our practices. Our convictions and impression of the real world, and the decisions we make, are, to an impressive degree, molded upon how others see and assess the world. Therefore, when we have to settle on a choice, we regularly search out the assessments of others. Opinions and their related concepts […]

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Spelling Correction in Python with TextBlob

Introduction Spelling mistakes are common, and most people are used to software indicating if a mistake was made. From autocorrect on our phones, to red underlining in text editors, spell checking is an essential feature for many different products. The first program to implement spell checking was written in 1971 for the DEC PDP-10. Called SPELL, it was capable of performing only simple comparisons of words and detecting one or two letter differences. As hardware and software advanced, so have […]

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Simple NLP in Python with TextBlob: N-Grams Detection

Introduction The constant growth of data on the Internet creates a demand for a tool that could process textual information in a faster way with no effort from the ordinary user. Moreover, it’s highly important that this instrument of text analysis could implement solutions for both low and high-level NLP tasks such as counting word frequencies, calculating sentiment analysis of the texts or detecting patterns in relationships between words. TextBlob is a great lightweight library for a wide variety of […]

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Fine-Grained Sentiment Analysis of Smartphone Review

How to conduct fine-grained sentiment analysis: Approaches and Tools Data collection and preparation. For data collection, we scraped the top 100 smartphone reviews from Amazon using python, selenium, and beautifulsoup library. If you don’t know how to use python and beautifulsoup and request a library for web-scraping here is a quick tutorial. Selenium Python bindings provide a simple API to write functional/acceptance tests using Selenium WebDriver. Let’s begin coding    

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Ultimate guide to deal with Text Data (using Python) – for Data Scientists and Engineers

Introduction One of the biggest breakthroughs required for achieving any level of artificial intelligence is to have machines which can process text data. Thankfully, the amount of text data being generated in this universe has exploded exponentially in the last few years. It has become imperative for an organization to have a structure in place to mine actionable insights from the text being generated. From social media analytics to risk management and cybercrime protection, dealing with text data has never […]

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Natural Language Processing for Beginners: Using TextBlob

Introduction Natural Language Processing (NLP) is an area of growing attention due to increasing number of applications like chatbots, machine translation etc. In some ways, the entire revolution of intelligent machines in based on the ability to understand and interact with humans. I have been exploring NLP for some time now.  My journey started with NLTK library in Python, which was the recommended library to get started at that time. NLTK is a perfect library for education and research, it becomes […]

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NLP Essentials: Removing Stopwords and Performing Text Normalization using NLTK and spaCy in Python

Overview Learn how to remove stopwords and perform text normalization in Python – an essential Natural Language Processing (NLP) read We will explore the different methods to remove stopwords as well as talk about text normalization techniques like stemming and lemmatization Put your theory into practice by performing stopwords removal and text normalization in Python using the popular NLTK, spaCy and Gensim libraries   Introduction Don’t you love how wonderfully diverse Natural Language Processing (NLP) is? Things we never imagined […]

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Sentiment Analysis in Python With TextBlob

Introduction State-of-the-art technologies in NLP allow us to analyze natural languages on different layers: from simple segmentation of textual information to more sophisticated methods of sentiment categorizations. However, it does not inevitably mean that you should be highly advanced in programming to implement high-level tasks such as sentiment analysis in Python. Sentiment Analysis The algorithms of sentiment analysis mostly focus on defining opinions, attitudes, and even emoticons in a corpus of texts. The range of established sentiments significantly varies from […]

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Simple NLP in Python With TextBlob: Tokenization

Introduction The amount of textual data on the Internet has significantly increased in the past decades. There’s no doubt that the processing of this amount of information must be automated, and the TextBlob package is one of the fairly simple ways to perform NLP – Natural Language Processing. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, tokenization, sentiment analysis, classification, translation, and more. No special technical prerequisites […]

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