Sentiment Analysis on

Android Lollipop Using

Twitter APIPedram Bashiri

Rohit Ruparel

Joseph Caprino

Introduction

• Huge growth in the use of microblogging platforms

such as Twitter

• Organizations mining Twitter for information

regarding what people think about their products

and services

• Twitratr (twitrratr.com), tweetfeel

(www.tweetfeel.com), and Social Mention

(www.socialmention.com) advertise sentiment

analysis

Overview

• Sentiment analysis on Google’s Android Lollipop

• We are using big data techniques to better do this

analysis

• Using Twitter API to download tweets

• Downloaded unique tweets from hashtags

#Android5 #AndroidLollipop as textiles

System Architecture

Achievements

• 30,000 unique tweets downloaded via Twitter4j

library interfacing with Twitter API

• Code checks for duplicate tweets and ensures

we have unique tweets

• Performed a word count analysis utilizing

MapReduce

Achievements

• Stored the results of the word counter utilizing

MapReduce into HBase

• Utilized HBase Java API

• Gathered the word count analysis data and

visualized it

Achievements

• Processed a number of tweets and determined

their sentiment

• Ignored “bad” tweets

• Utilized Stanford Core NLP for sentiment analysis

on remaining tweets

• Saved results of scores and their frequency

• Visualized the sentiment analysis results

Issues

• Sentiment Analysis:

• Ads without URLs captured

• Scores differ for almost identical tweets

Future Work

• Distributed sentiment analysis

• More advanced visualizations

• Creating our own dictionary to do sentiment

analysis

Demo