abinj / twitter-sentiment-analysis

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.