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Twitter Sentiment Analysis

Sentiment analysis refers to identifying as well as classifying the sentiments that are expressed in the text source. Tweets are often useful in generating a vast amount of sentiment data upon analysis. These data are useful in understanding the opinion of the people about a variety of topics.
Twitter Sentiment Analysis

The Internet has become a platform for online learning, exchanging ideas, and sharing opinions. Social networking sites like Twitter, Facebook, Google+ are rapidly gaining popularity as they allow people to share and express their views about topics, have discussions with different communities, or post messages across the world. There has been a lot of work in the field of sentiment analysis of Twitter data.

Sentiment analysis can be defined as a process that automates the mining of attitudes, opinions, views, and emotions from text, speech, tweets, and database sources through Natural Language Processing (NLP). Sentiment analysis involves classifying opinions in text into categories like "positive" or "negative" or "neutral". It's also referred to as subjectivity analysis, opinion mining, and appraisal extraction. The words opinion, sentiment, view, and belief are used interchangeably but there are differences between them.

1. Opinion: A conclusion open to dispute (because different experts have different opinions )

2. View: subjective opinion

3. Belief: deliberate acceptance and intellectual assent

4. Sentiment: opinion representing one's feelings.

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