Twitter Big Data Projects

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Twitter Big Data Projects

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About Twitter Data:

• It holds huge amount of data
• Million tweets plus meta data available
• It is in JSON format
• It can perform some basic big data analysis on the large dataset

          -Tweetiest time zones

          -Busiest zones

          -Common hashtags

Challenges of Twitter Data:

Learning language

• Unix+SQL
• Python
• Tweet API

Dynamic Lookups

• Filtering junk

          -Justin Bieber

          -Prepositions and pronouns

          -FTW, FML and LOL

• Normalizing output

          -Android Mobile Browser

          -Twitter for Android

          -Android 4.0.XXX

Big data Analytics

• Data storage
• Data processing
• Data classification

Why we go for Twitter Data?

    Twitter data is more personal, open and expensive for all users. Twitter is a gold mine of data social platform to tweet all users tweets that are pull or public completely. Due to this benefit, a large amount of data gets and run on big data analytics tool. We can pull certain tweet topic within the last 20 minutes or we can pull certain users non-retweeted tweets using Twitter’s API. Through this analysis, we can perform

• Sentiment Analysis,
• Syntax Analysis Applications
• Entity Recognition Analysis
• Frequency Analysis
• Segmentation Or Categorization
• Emotion Level Computation
• Anomaly Detection Algorithms
• Geo Location Based Transportation Systems
• Correlation Analysis (Spatial And Temporal)
• Spatial Traffic Information

 Tools to Analysis Twitter Big Data:

• Apache S4
• BirdSong Analytics
• Cyfe
• NodeXl
• TWChat
• TweepsMap
• Audiense
• Keyhole
• Twitonomy
• Twenty Feet
• Twitter Counter
• Visible Tweets
• Tweetstats
• Twistori
• Tweepsmap
• Python 2.7 [Python library called “Tweepy” is used]
• Hadoop Mahout [Service provider is used]
• Combination of two technologies [R and Hadoop]
• Tweeter Streaming API
• StreamReduce [Apache Storm]

Techniques/Methods to Analysis Twitter Data:

• Opinion mining approach
• Emotion detection approaches
• Latent Dirichlet Allocation
• Knowledge Extraction Technique
• Lexicon based method
• Naïve Bayes Classifier
• Clustering algorithms

Current Twitter Big Data Projects Topics:

• Support Advanced Big Data Analytics Using Big Social Data Multidimensional Mining
• Natural Epidemics and Events Characterization from Twitter
• Social Data and Conventional Network for Detect Real-Time Earthquake
• Visual and Textual Features for Twitter Photo Geo-Localization
• Large Scale Bipartite Rating Graphs Using Scaling Collaborative Filtering by Spark and Lenskit
• Dependable Services Using Time Series Anomaly Detection in Cloud Computing Systems
• Top-K Item Frequency and Frequent Items Through Any Sizes Sliding Windows
• Spatial Traffic Information Based Twitter Sources in Big Data Enabled Self-Organizing Networks
• Word Embedded Based Clustering to Survey Public Health From Social Media for Twitter Classification
• Evaluate Mahout Clustering Algorithms Performance Using Twitter Streaming Dataset
• Normalize Informal Short Text Messages Using Semi-Supervised Probabilistic Method
• Clustering Appearance Patterns for Detect the Automated Cyber Bullying
• Twitter Data Visualization and Analysis Using R Language on Hadoop Framework
• Using Scalable Uncertainty Aware Discovery Scheme Cyber Physical Systems in Big Data Sensing Applications
• Big Social Data for Earthquake Consequences Now-casting