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40

Lectures

53

Course Duration

Unlimited Duration

Updated

August 12, 2022

Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
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Ayesha Tahir
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Sentiment analysis is a natural language processing (NLP) technique used to determine whether data is positive, negative or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs.

Sentiment analysis studies the subjective information in an expression, that is, the opinions, appraisals, emotions, or attitudes towards a topic, person or entity.

Sentiment analysis tools are essential to detect and understand customer feelings. Companies that use these tools to understand how customers feel can use it to improve CX. Sentiment analysis tools generate insights into how companies can enhance the customer experience and improve customer service.

    • Theory Unlimited
    • What is the Twitter Sentiment Analysis? Unlimited
    • Why Twitter Sentiment Analysis? Unlimited
    • Getting Data from Twitter Streaming API Unlimited
    • Get access to the Twitter API Unlimited
    • Case Study – Data Gathering from Twitter for Sentiment Analysis Unlimited
    • Summary Unlimited
    • Assignment Unlimited
    • Theory Unlimited
    • Approach To Analyze Various Sentiments Unlimited
    • Let’s Guess some tweets Unlimited
    • Data Summary Unlimited
    • Exploratory Data Analysis Unlimited
    • Data Cleaning Unlimited
    • Target Labels Unlimited
    • Textblob Unlimited
    • Summary Unlimited
    • Assignment Unlimited
    • Theory Unlimited
    • What is Natural Language Processing? Unlimited
    • What is NLTK? Unlimited
    • Techniques of Text Preprocessing using NLTK library Unlimited
    • Named Entity Recognition (NER) Unlimited
    • Parts Of Speech Tagging (POS Tagging) and Chunking Unlimited
    • Named Entity Recognition (NER) Unlimited
    • AIM Unlimited
    • Stemming Unlimited
    • Lemmatization Unlimited
    • Stop Words Unlimited
    • POS tagging Unlimited
    • Name Entity Recognition Unlimited
    • Summary Unlimited
    • Assignment 1 week, 3 days
    • Theory Unlimited
    • Word Vectorization (World Embedding) Unlimited
    • Term Frequency – Inverse Document Frequency (TF – IDF) Unlimited
    • Bag of Words Unlimited
    • TF-IDF Unlimited
    • Import Necessary Dependencies Unlimited
    • Read and Load the Dataset Unlimited
    • Data Preprocessing Unlimited
    • Removing the stopwords Unlimited
    • Removing Emoji’s Unlimited
    • Removing the special characters Unlimited
    • Removing the Punctuations Unlimited
    • Cleaning the repeated characters Unlimited
    • Removing the URL’s Unlimited
    • Data Visualization Unlimited
    • Word Vectorization Unlimited
    • Train and Test Split Unlimited
    • Bayes’s Theorem Unlimited
    • Summary Unlimited
    • Assignment 1 week, 3 days

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