Twitter-Sentiment-Analysis
Analyse the sentiment of tweets using Java
Requirements
1) twitter4j
https://mvnrepository.com/artifact/org.twitter4j/twitter4j-core/4.0.6
2) Stanford Core NLP
-stanford-corenlp
-stanford-corenlp-models
What is Sentiment Analysis?
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
It’s also known as opinion mining, deriving the opinion or attitude of a speaker.
A common use case for this technology is to discover how people feel about a particular topic.
Phase 1 - Creating a Twitter App
-Gto to https://apps.twitter.com and create an app
-Get the following informations
oauth.consumerKey=<api-key-for-your-app>
oauth.consumerSecret=<api-secret-for-your-app>
oauth.accessToken=<access-token>
oauth.accessTokenSecret=<access-token-secret>
Phase 2 - Setup Tweets Manager
By using the creadentials we can query and fetch tweets with the help of twitter4j library.
Phase 3 - Sentiment Analyzer
This class initializes the pipeline and findSentiment which takes in a tweet as input
and returns it’s sentiment score.
scale of 0 = very negative, 1 = negative, 2 = neutral, 3 = positive, and 4 = very positive.