Notes:
Sentiment analysis, also known as opinion mining, is the process of identifying and extracting subjective information from text or other forms of data. It involves analyzing the language and tone of a piece of text to determine the overall sentiment or emotion that is being expressed.
There are several ways that sentiment analysis can be performed, but one common approach is to use natural language processing (NLP) techniques to identify and classify words or phrases that are associated with particular emotions or sentiments. For example, words like “happy,” “excited,” and “thrilled” might be classified as positive, while words like “sad,” “angry,” and “depressed” might be classified as negative.
Once the sentiment of individual words or phrases has been identified, the overall sentiment of a piece of text can be determined by analyzing the overall balance of positive and negative words or phrases. For example, if a piece of text contains more positive words than negative words, it might be classified as having a positive sentiment.
Sentiment analysis is often used in a variety of applications, including social media analysis, customer service, and market research. It can provide valuable insights into the opinions and emotions of people, and can be used to help understand and respond to customer needs and preferences.
Wikipedia:
See also:
Sentiment Analysis & Dialog Systems 2017 | Sentiment Analysis Tools (Open Source) & Dialog Systems
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- How you can use sentiment analysis for better customer engagement – RubyConf Indonesia 2017
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- Sentiment Analysis Tutorial – Examples of How Sentiment Analysis Works
- Twitter live sentiment Analysis Tutorial in Python – Tweepy and TextBlob
- How to Do Sentiment Analysis – Intro to Deep Learning #3
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- How to Time the Markets Using Mass Psychology and Sentiment analysis
- Machine Learning: How to Install Python Machine Learning for sentiment analysis
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- Intro to Text Mining Sentiment Analysis using R-12th March 2016
- Sentiment Analysis in R | R Tutorial | R Analytics | R Programming | What is R | R language
- How Oracle Uses CrowdFlower For Sentiment Analysis
- Brand Monitoring Part 2 – How to Apply Sentiment Analysis to Tweets
- Swift programming language tutorial: Sentiment Analysis with HP IDOL On Demand
- How to Conduct Sentiment Analysis #brandwatchtips
- Timea Turdean – Intro to Sentiment Analysis – WTM Vienna 2014
- How to do real-time Twitter Sentiment Analysis (or any analysis)
- Mobile Sentiment Analysis – How mobile conversation is different
- AT&T Bootstrap Tutorial: Mobile Applications with a Text/Sentiment Analysis API
- Big Data Week – Data Science London – Alex Davies “Sentiment Analysis or how to find happiness”
- How to add sentiment analysis via Influencer Monitor
- Adstare Product Tutorial – Facebook Sentiment Analysis