This document discusses analyzing social media data from Meetup.com using graph technologies. It describes retrieving data via the Meetup API, modeling the data as a graph, analyzing the graph using algorithms and tools like PGX and PGQL, and visualizing results in Cytoscape. Potential questions that could be answered include identifying influential people and groups, relationships between groups, and hot topics. The demo environment uses Oracle Big Data Lite with Oracle NoSQL Database to store the graph and analyze it.

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Visual Analysis of Social Media Data from
Meetup.com using Graph Technologies
code.talks 2018 | October 18/19, 2018 | Hamburg
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Karin Patenge | Principal Solution Engineer | BU Cloud & Core Technologies
@kpatenge | karin.patenge@oracle.com | www.slideshare.net/kpatenge
Oracle Deutschland B.V. & Co. KG

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Data of Interest
• Data retrieval via REST API
https://www.meetup.com/meetup_api
• Different API methods & versions
• API Key required
• Sample request
• Data returned as JSON
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Direct relations not (yet) analyzed
is_interested_in
is_member_of
is_assigned_to
has_registered_for
is_located_in
is_located_in
takes_place_at
Venue

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Potential Questions of Interest
• Which Meetup groups are most active in terms of:
– # members
– # events
– # event attendees
• Who and where are influencers in the Meetup community?
• Where are connections between the Meetup groups in different locations?
• Which topics are “hot” and where?
• How close/similar are groups?
• …
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Modeling Data as Graphs
The more connected the data is, the better a Graph fits
Graphic source: http://www.ateam-oracle.com/intro-to-graphs-at-oracle/
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• A set of nodes (aka vertices)
– each vertex has a unique identifier
– each vertex has a set of in/out edges
– each vertex has a collection of key-value
properties
• A set of edges
– each edge has a unique identifier
– each edge has a head/tail vertex
– each edge has a label denoting type of
relationship between two vertices
– each edge has a collection of key-value properties
• Blueprints Java APIs
• Implementations
– Oracle (Spatial and Graph, Big Data Spatial and
Graph), Neo4j, DataStax (Titan), InfiniteGraph,
Dex, Sail, MongoDB, …
What is a Property Graph?
https://github.com/tinkerpop/blueprints/wiki/Property-Graph-Model
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• PageRank, Weighted PageRank
– Find influencers, critical vertices
• Personalized PageRank
– Find important people/products/...
with respect to a given starting point
• Sparsification
– Trim down the graph to make it more
fragmented
• Clustering
– Find communities which can be the
basis of segmentation, and/or
recommendation/anomaly detection,
churn analysis
• Centrality
– Find critical people/devices/...
• Shortest path
– Discover links, find suspect‘s close
collaborators, transportation routing
• Breadth-First-Search (BFS)
– Impact analysis, link analysis
• Matric factorization
– Recommendation
• Reachability
– Connectivity test
• ...
Graph Algorithms and their Applications

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Architecture of Property Graph Support
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Graph Data Access Layer (DAL)
Graph Analytics
Blueprints & Lucene/SolrCloud RDF (RDF/XML, N-
Triples, N-Quads,
TriG,N3,JSON)
REST/Web
Service/Notebooks
Java,Groovy,Python,…
Java APIs
Java APIs/JDBC/SQL/PLSQL
Property Graph
formats
GraphML
GML
GraphSON
Flat FilesScalable and Persistent Storage Management
Parallel In-Memory Graph
Analytics (PGX) /
Graph Querying (PGQL)
Oracle NoSQL
Database
Oracle RDBMS Apache HBase
Apache
Spark
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PGX
• Toolkit for In-Memory, Parallel Graph
Analysis containing
– PGX shell
– Analyst API with a large collection of built-in
algorithms (45+)
– Tutorials and more
• Developed by Oracle Labs
• https://docs.oracle.com/cd/E56133_01/latest/i
ndex.html
• https://event.cwi.nl/grades/2018/07-
VanRest.pdf
PGQL – Property Graph Query Language
• http://pgql-lang.org/
• Graph Pattern Matching combined with
SQL
• Developed by Oracle Labs
• Proposed for standardization
• Changes in Version 1.1:
http://pgql-lang.org/spec/1.1/#breaking-syntax-
changes-since-pgql-10
Property Graph Analytics Engine
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Data Processing and Analysis Workflow: Overview
Retrieve&Prepare
Prepare
source data
• Using R for data
retrieval via
REST API and
conversion
JSON  CSV 
OPV/OPE
Load&Build
Load
nodes and
edges data
into a graph
• Using Oracle
NoSQL DB as
Graph data
store
Analyze
Analyze
graph data
• Using Graph
Analytics Engine
(PGX) and
Property Graph
Query Language
(PGQL)
Visualize
Visualize
graph data
• Using
Cytoscape
Results
Summarize
results
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My Demo Environment
• Available for free:
Oracle Big Data Lite VM 4.11 running in Oracle VirtualBox
– Big Data Spatial and Graph (BDSG) 2.5 including Property Graph Query Language
(PGQL) 1.0
http://www.oracle.com/technetwork/database/bigdata-appliance/oracle-bigdatalite-2104726.html
• Gremlin, Apache Groovy Shell
• Zeppelin Notebook with PGX Interpreter
– Oracle NoSQL Database (Minimal instance with 1 node, no replication, aka kvlite)
– RStudio
• Several R packages loaded
– Cytoscape 3.6.0
• Big Data Spatial and Graph 2.4 support installed
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Demo

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Summarize (Preliminary) Results
✓Who are important people in the Meetup landscape?
✓Which Meetup groups should we talk to for certain topics?
✓Which Meetup groups are relevant in terms of
#Members, #Participants of events, #Events
✓Which Meetup groups are related and how?
✓...
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Key Takeaways – So far
• Graph data model perfect to focus on connectivity
• Code written once, re-useable many times to retrieve data from every
desired location (city)
• Visual analysis helps a great deal to understand how data are connected
• Big variety of analytic tools and frameworks to answer all kind of questions
– Integrated distributed, in-memory graph analytics engine
• Use case of how to combine Open Source with Oracle Technologies
• Please also check latest Graph talks during
Analytics and Data Summit in March 2018
– https://analyticsanddatasummit.org/schedule/
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Follow us @kpatenge @SpatialHannes @JeanIhm
karin.patenge@oracle.com
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Blogs:
https://blogs.oracle.com/bigdataspatialgraph/
https://blogs.oracle.com/oraclespatial/
AskTom Office Hours for Property Graph:
https://asktom.oracle.com/pls/apex/f?p=100:551