Lecture 7 - The University of Texas at Dallas

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Transcript Lecture 7 - The University of Texas at Dallas

Analyzing and Securing
Social Networks
Web Data and Semantics in Social
Network Applications
Dr. Bhavani Thuraisingham
September 11, 2015
4/8/2017 02:32
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Outline
0 Reference: P. Mika, Semantic Web and Social Networks,
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Springer, 2008: Chapter 3, 4, 5, 6
Electronic Sources for Network Analysis
Knowledge Representation on the Semantic Web
Modeling and Aggregating Social Network Data
Developing Social Semantic Applications
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Electronic Sources for Network Analysis
0 Electronic Discussion Networks
0 Blogs and Online Communications
0 Web-based Networks
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Electronic Discussion Networks
0 Communication among employees using email archive
0 Email networks
- E.g., Enron email network analysis
0 Build network from the email communications
0 Public forums and email lists
0 Group communication
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Blogs and Online Communications
0 Content analysis of blogs (web logs)
0 Trend analysis of blogs
0 Online social networks
- Facebook, Twitter, LinkedIn, Foursquare
0 Sentiment analysis
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Web-based Networks
0 Web pages from a network
0 Contents of web pages
0 Mine and analyze the web pages
0 Web Mining
- Web content mining
- Web structure mining
- Web log mining (who visited the web pages)
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Knowledge Representation on the Semantic Web
0 Ontologies and their role in the semantic web
0 Ontology languages for the semantic web
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Ontologies and Their Role in the Semantic Web
0 Ontologies are expressed in formal languages with well-
defined semantics
0 Ontologies build upon a shared understanding with a
community
0 RDF and OWL are languages for the semantic web
0 More expressive languages have less reasoning power
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Ontology Languages for the Semantic Web
0 RDF
0 RDF Schema
0 RDF Vocabulary
0 RDF and FOAF
0 RDF and Semantics
0 SPARQL (query language for RDF)
0 OWL – Web Ontology Language
0 Comparison to UML and the ER Model
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Modeling and Aggregating Social Network Data
0 Network Data Representation
0 Ontological Representation of Social Individuals
0 Ontological Relationship of Social Relationships
0 Aggregating and Reasoning with Social Network Data
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Network Data Representation
0 Graphs
0 Matrices
0 Number the nodes and use the numbers to represent the
edges (e.g., 12 means edge between nodes 1 and 2)
0 GraphML (XML for graphs)
0 Do not support the aggregation of network data
0 Key challenges: Identification and Disambiguation
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Ontological Representation of Social Individuals
0 FOAF is an example of an ontological representation of
individuals
0 Eliminates the drawbacks of early social networks like
Friendster, Orkut
0 The early social networks had centralized control and were
difficult to manage
0 FOAF is distributed and has a rich ontology to characterize
individuals
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Ontological Representation of Social
Relationships
0 Social networks such as FOAF need to be extended to
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support relationships
Support the integration of social information
Integrates/aggregates multiple social networks
Properties of relationships
- Sign: Positive or Negative relationships
- Strength (e.g., frequency of contact)
- Provenance (different ways of viewing relationships)
- Relationship History
- Relationship roles
Conceptual models for social data – semantic net, RDF
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Aggregating and Reasoning with Social Network
Data
0 Representing Identity
- URI (Universal Resource Identifier)
- Disambiguation (A and B are the same; There are two
people called John Smith)
- OWL has the “sameAS” property
0 Equality
0 The property sameAs is reflexive, symmetric and transitive
0 Descriptive Logic vs. Rule based reasoners
- Rule based reasoners use forward chaining and backward
chaining
- Descriptive logic is used for classification and checking
for ontology consistency
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Developing Social Semantic Applications
0 Building Semantic Web Applications with Social Network
Features
0 Flink: The Social Network of the Semantic Web Community
0 Openacademia: Distributed semantic web-based publication
management
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Building Semantic Web Applications with Social
Network Data
0 General Architecture
- Sesame for storage and reasoning (alternative is Jena)
= Sesame manages the data sources
- Sesame Client API
- Querying through SPARQL
- Elmo and associated tools for building ontologies and
interfacing to RDF data
0 Social Network Applications (e.g., FLINK) are built on top of
the architecture as applications
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Flink: The Social Network of the Semantic Web
Community
0 Flink was developed by Peter Mika; it is a semantic web
representation of any online social data
0 Current instantiation uses semantic web researchers are
nodes and their collaboration as links
0 Visualization tools for visualizing the nodes and links
0 Flink social networks are decomposed and stored as RDF
triples and managed by Sesame
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Openacademia: Distributed Semantic Web-based
Publication Management
0 Openacademia is a social network application for maintaining
scientific publications
0 Data from multiple data stores (e.g., FOAF profiles,
publications) and access via Elmo crawler
0 Data converted into RDF and managed by Sesame
0 Openacademia servlet queries Sesame (SPARQL queries) and
aggregates the data and presents to the user