Social Learning and Knowledge Sharing Technologies Lecture Slides about Social Patterns & Graph Theories

© author(s) of these slides including research results from the KOM research network and TU Darmstadt; otherwise it is specified at the respective slide
31-Oct-14
Dr.-Ing. Johannes Konert
Dr.-Ing. Christoph Rensing KOM - Multimedia Communications Lab
Template Teaching v.3.4
KnowShare__3_SocialDesignPatterns_GraphTheory__2014.10.31__v1.1.pptx
Social Patterns & Graph Theories Basics
Social Learning and Knowledge Sharing Technologies
31.10.2014
1. Theories and Challenges
2. Structures and Pattern
Modeling Context
4. Context- Awareness
Search
Context Detection
3. Services and Mechanisms
Peer Tutoring Collabora. Tasks
Contextual Services
5. Evaluation
Foundations and Learning Theories
Challenge: Resource Selection & Navigation
Challenge: Coopera- tion & Collaboration
Challenge: Feedback & Targeting
Peer Assessment & Feedback
Learning Analytics
Learning Path Transparency
Offline Evaluation
Hypothesis validation
Formative and summative
Resources
Social Patterns
Graph Theory Basics
Scripted Collaboration
Re- com- men- der
Human
Resource
User / Learner

KOM – Multimedia Communications Lab
2
Approaches to Modern Web Application Development MVC, ACID, CRUD REST, LAMP <-> MEAN, PaaS
Social Media Systems Design Aspects
Content vs. User
Relationship Types
Roles, Levels, Badgets, Achievements as an instrument for Guidance
Responsibility and Democracy
Ambient Intimacy
Graph Theory Basics What have subways, emails and rivers in common? (or users, tags, resources)
Image sources: http://www.seawaterfoundation.org/siteImages/rivers_art.jpg,, http://vnfa8y5n3zndutm1.zippykid.netdna-cdn.com/wp-content/uploads/2011/12/url7.jpg, http://images.all-free- download.com/images/graphiclarge/s_bahn_71263.jpg, http://de.roblox.com/item.aspx?seoname=U-Bahn&id=28172595, http://faculty.kutztown.edu/rieksts/225/graphs/tripartite_files/image002.jpg,
Lecture 3 Social Patterns & Graph Theories Basics

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Motivation
1. Challenge: Resource Selection & Navigation
4. Challenge: Cooperation & Collaboration
2. Challenge: Targeting
(How to find resources? How to navigate?)
How to motivate to reach learning goals?
Modern Web App Dev (Basics)
Social Systems Design Patterns
Graph Theory (Basics)
3. Challenge: Feedback
(How to design Peer Feedback/Assessment?)
(What is the path to the goal?)
(Who is the best candidate?)
How to establish a “community” sense?
Challenges
How to tell “what’s next”?

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At the end of the lecture / exercise you will be able…
Learning objectives of lecture 3
..to repeat aspects to keep in mind when designing a new Social Learning and Knowledge Sharing System.
..to decide based on the aspects which components you want to use.
..to select and focus on specific Social System Design Patterns to support your system characteristics.
..to differentiate (basic) types of graph representations and you can decide and explain to which type example graphs belong to

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Approaches to Modern Web Application Development
Image source: ok/FreeDigitalPhotos.net
Placement in the context of the lecture
Modeling Context
Search
Context Detection
Contextual Services
5. Evaluation
Learning Analytics
Offline Evaluation
Resources
Social Patterns
Graph Theory Basics
Re- com- men- der
Human
Resource
User / Learner

6
Codecademy Airbnb
Examples of Modern Web Applications
Characteristics (some..)
Changes in one GUI widget cause reload/filtering of data in other app parts
Far beyond text-based websites
Responsive Layout

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.. with Web Application we mean: an application running (and displayed) in the browser
.. with Modern we mean: system design solutions supporting development, maintenance, performance and responsiveness of web applications beyond and in contrast to websites.
..with Approaches we mean: Technologies and Paradigms used to develop Modern Web Applications (this excludes hardware and runtime maintenance aspects) Components of a Modern Web Application
Image source: http://www.codeproject.com/Articles/645753/Challenges-and-solutions-Architecture-of-a-Modern
Approaches to Modern Web Application Development
Distributed System(s)
..so forget this illustration

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Web server
Components of a (Modern) Web Application
Image sources: http://www.computero.com/media/HP-server.jpg, DryIcons/Shine, Tango IconSet
Server
Client
Operating System (OS)
Script language
DB
Model
Controller
<!DOCTYPE html> <html>..</html>
View
Web browser
Script language
Local state

10
MVC (Pattern)
Model encapsulates the data (objects) state
View displays the data, is user interface and allows user actions
Controller reacts on user actions, coordinates model(s) and system communication
Modern Web Applications
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View

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MVC (Pattern)
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View

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ACID (Database Design Properties)
Atomicity (all or nothing)
Consistency (constraint-based valid states)
Isolation (concurrency control)
Durability (no loss after commit)
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View

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CRUD (Persistent Storage [Interface] Properties)
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View
Operation
SQL
HTTP
Create
INSERT
PUT / POST
Read (Retrieve)
SELECT
GET
Update (Modify)
UPDATE
PUT / PATCH
Delete (Destroy)
DELETE
DELETE
Web Service / API

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REST (Property)
Representational state transfer
Stateless server & cachable responses
uniform ressource and service addresses
Alternative representations (?)
Interface-based operations (identify, create, modify, delete) New aspects:
Hypermedia as state transition machine
Using many HTTP methods
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View
Web Service / API
HTTP-based example: http://www.airbnb.com/places
public class MyPlaces {
@GET
@Produces(MediaType.TEXT_PLAIN)
public String getIt() {
return "Darmstadt, Frankfurt, München";
}
@GET
@Produces(MediaType.APPLICATION_JSON)
public String getIt() {
return "{ ‘places‘: [‘Darmstadt‘,‘Frankfurt‘,‘München‘]}";
}
}

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LAMP (Paradigm)
Linux OS
Apache Webserver
MySQL DB
PHP Server-side Language (Also popular as XAMP or XAPP)
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View
Web Service / API

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MEAN (Paradigm)
Node.js operating language
Express Webserver framework
MongoDB NoSQL storage
AngularJS client-binding (Also known as AMEN)
Web server
Server
Client
Script language
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View
Web Service / API
New aspects:
MEAN adds a client-layer component to the stack
All JavaScript

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Total number based on Wikipedia entries on ‚database‘, ‚webserver‘, ‚web application framework‘,… from 2014-10-29 (only to get a idea of dimensions)
Modern Web Application Development
Database (~50)
Webserver (~30)
Server: Web App Framework (~130)
Template Engine (~90)
Client: Web App Framework (JS: ~40)
SQLite
HyperSQL
MySQL
PostgreSQL
Cassandra
MongoDB
(Microsoft IIS)
Apache HTTP
Apache Tomcat
Jetty
Boa
NginX Mongoose WS
lighttpd
(Node.js)
Full solution frameworks: ASP.NET MVC, GWT
PHP (CakePHP, Zend)
Ruby (on Rails)
Python (Django, Pyramid)
Java Servlets (Spring, JSF, Struts)
ExpressJS
PHP / Smarty
Genshi
Cheetah
Mustache
JSP
Jade
Dojo
MochiKit
script. aculo.us
ExtJS
YUI
Qooxdoo
jQuery
Ember.js
AngularJS

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PaaS (Pattern)
Platform as a Service
Cloud-Service model for delivery of a (scalable, reliable) operating platform for applications
Client creates and maintains application
Web server
Server
Client
DB
Web browser
Script language
Local state
Model
Controller
View
Model
Controller
View
Web Service / API
Script language
https://www.heroku.com/
https://cloud.google.com/appengine/
https://www.openshift.com/

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Social System Design Patterns
Image and book reference: http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925, http://www.amazon.com/Building-Social- Applications-Gavin-Bell/dp/0596518757/
Placement in the context of the lecture
Modeling Context
Search
Context Detection
Contextual Services
5. Evaluation
Learning Analytics
Offline Evaluation
Resources
Social Patterns
Graph Theory Basics
Re- com- men- der
Human
Resource
User / Learner

20
“The main issue with designing and maintaining a social web application is not the technology, it’s the psychology as people and their activities are the core of the application.”
The quote is no citation of other authors, but written by JK based on [Crumlish et al 2009] and [Bell 2009]
The main issue

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Overview on Social System Design Aspects
1. Challenge: Resource Selection & Navigation
4. Challenge: Cooperation & Collaboration
2. Challenge: Targeting
3. Challenge: Feedback
How to motivate to reach learning goals?
How to design Peer Feedback/Assessment?
How to establish a “community” sense?
How to tell “what’s next”?
Content vs. User
Roles, Levels, Badges, Achievements
Responsibilities and Democracy
Relationship Types
Ambient Intimacy

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Publisher-led
Product-led
Interest-Led
Image sources: taken screenshots from each website on 29.10.2014
Structural Patterns
Content vs. User

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Publisher-led
Product-led
Interest-Led (hybrids exist)
Image sources of examples: taken screenshots from each website on 29.10.2014
Structural Patterns
Content vs. User
Publisher
Publisher
Interest
Interest
Interest
Product

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Content-centric
User-centric
Event-centric
Structural Patterns
Content vs. User

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Content-centric
User-centric
Event-centric (hybrids exist)
Structural Patterns
Content vs. User
Content (Event)
Content
Event
Content (User)
User (Content)
User

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Publisher
Product
Interest
Content
Media Syndication
Customer Exchange
Learning/Sharing
Event
Marketing
Franchise
Gathering/Exchange
User
VIP Promotion
Grouping
Friendship
Illustration by J.Konert, no specific reference for these dimensions, but see [Bell2009, p. 123ff] for aspects
Structural Patterns
Most interesting for Social Learning and Knowledge Sharing are
Interest-led
Content-centered
Content vs. User

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(some relationship arrows are omitted for better readability)
Image source: Tango Icon set,
Relationship Types
Relationship Types
Site owner
Users
Users
Resources
Conversation
Meta-Data Categories Tags
Groups
Friendship
Following
Following
Bookmarking
Following
Ownership
Ownership
Sharing
Sharing
Following
Ownership
Sharing
Ownership
Following

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Technically
Symmetric relationships
Discovery of people/groups
Request, Acknowledgement, Decline, Ignore, Remove
Asymmetric relationships
Follow (Fan), Unfollow, Bookmark
Filter
Structure and Content creation
Group creation, deletion, handover ownership
Content creation, deletion, (remaining after account deletion)
Tagging
Privacy and Visibility settings for user-data, content, structures
Search and Recommendation (PULL, PUSH)
Administration (reporting, deletion, reasoning, explanation) [see later slides]
See [Crumlish et al, 2009], p.354-379 for further details. * read http://socialseriousgames.de/post/5437302687/social-serious-gaming-chi-2011-impressions for further details
Relationship Types
Make content and profile creation easy, syndicate and recommend this technically and allow structure to emerge later on
[cf. Crumlish et al., p378]
Symmetric
Asymmetric

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What is reputation? It’s the general opinion (judgment) (more technically, a social evaluation) of (and by) the public (or a group or only a person) towards an entity (person, organization, object or group of entities) – as distinct and different from the background (others) – concerning the likelihood of the entity to behave in a certain way in the future [under certain circumstances]. It is a ubiquitous, spontaneous and highly efficient mechanism of social control. [Crumlish et al. 2009, p. 153], citing Ted Nadeau “Reputation 2.0” Good. So let’s give people something that helps for reputation. Consider
Cooperativeness vs. Competitiveness
Comparability
Quality vs. Quantity
Honor User Loyalty and Progress

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Named Levels
Reflect the experience (and/or reputation) Usual measures are
Activities
Likes/Follower
Completion of tasks/quests (if applicable) (similar, but not ordered, are badges (or labels).. ..given for specific behavior or characteristics..can be extended endlessly)
Newbie
Active member
Contri- butor
Trend setter
Expert
Leader
Enthusiast

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Achievements (or Awards)
Reflects accomplished activities
Used to encourage quality over quantity behavior
Common
Can be reversible
Seldom
Can be unexpected and hidden
Image source: Konert 2014, .p 67; cf. Konert et al. 2013, Crumlish 2009, p. 166ff

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Image source: https://s3.amazonaws.com/codecademy-blog/assets/intro-new-profile/whole_page.jpg
Example: codecademy.com Profile
Qualitative, single, static Achievements
Badgets for specific skills
Points (as a kind of level)

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A Social Web Application should
offer a unique, protected identity (by email or OpenID etc.)
offer privacy settings (reasonable defaults, private, protected, public profile and activities)
enforce community guidelines (code of conduct)
grow organically (managed by owner and community)
provide tools for collective governance (reports, privileges, isolation, timed bans, ..)
allow collaborative filtering (votes, tagging)
never forget that all data belongs to the users (and that this implies rights to it)
Cf. [Bell, 2009, p. 209-224], [Crumlish et al, 2009, p. 383-397]; image taken from https://info.yahoo.com/legal/sg/yahoo/comms/
Responsibilities

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User-generated content administration “Duty of housekeeping” Easy content creation benefits
Diversification: more variety, specificity, more use/benefits for users
Identification: own content supports emotional binding Iceberg effect:
Lot of content with low quality (that should remain under the surface)
..and: illicit content (18+, NS-symbols, ..) Solutions:
Youth protection
Content administration
Algorithmic Quality assessment
Responsibilities
Quality of content
Amount
Acceptable quality
Image source: hhttp://www.vertriebslexikon.de/bilder/Eisberg-2009.jpg

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Responsibilities
User-generated content administration A little bit of German law (selection)
Operator is not responsible for law infringement of users
But operator must react promptly, if informed
§10 TMG - Speicherung von Information
Diensteanbieter sind für fremde Informationen, die sie für einen Nutzer speichern, nicht verantwortlich, sofern
(1) sie keine Kenntnis von der rechtswidrigen Handlung oder der Information haben und ihnen im Falle von Schadensersatzansprüchen auch keine Tatsachen oder Umstände bekannt sind, aus denen
die rechtswidrige Handlung oder die Information offensichtlich wird, oder (2) sie unverzüglich tätig geworden sind, um die Information zu entfernen oder den Zugang zu
ihr zu sperren, sobald sie diese Kenntnis erlangt haben.
Satz 1 findet keine Anwendung, wenn der Nutzer dem Diensteanbieter untersteht oder von ihm
beaufsichtigt wird.
§1004 BGB - Beseitigungs- und Unterlassungsanspruch (1) Wird das Eigentum in anderer Weise als durch Entziehung oder Vorenthaltung des Besitzes beeinträchtigt, so kann der Eigentümer von dem Störer die Beseitigung der Beeinträchtigung verlangen. Sind weitere Beeinträchtigungen zu besorgen, so kann der Eigentümer auf Unterlassung klagen. (2) Der Anspruch ist ausgeschlossen, wenn der Eigentümer zur Duldung verpflichtet ist.

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Responsibility of Content Administration
User-generated content administration
Setting up prompt reaction and administration of content
Categories of procedures for administration of UGC*
Algorithm-based
User-based
Operator-based
Requirements to procedures for administration of UGC*
Correctness of taken decisions (to delete)
Cost efficiency
Speed of decision taking in each single case
Amount of content that can be processed
Complexity of content that can be processed
*UGC = user-generated content

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Operator-based
User-based
Algorithm-based
Central
e.g. SecondLife
e.g. Knuddels
e.g. Chatsystems
Distributed
?
e.g. Wikipedia
e.g. P2P Sharing

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Operator-Based Responsibility (Complex-Decision)
User-Based Intermediation (Fuzzy-Decision)
Algorithm-Based Mass-Processing (Pre-Decision)
Complexity of content
Amount of Content that can be processed
Examples:
 Email complaints
 Claim button
 Word detection (NLP)

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Ambient Intimacy
Key aspect for social learning success (beside serendipity)
“..is about being able to keep in touch with people with a level of regularity and intimacy that you wouldn’t usually have access to, because time and space conspire to make it impossible.” *
Removing cold ambience and the feeling of being with others using the application may dramatically increase app stickiness and in the context of SLKST the learning success (as it is mainly about self-regulation, continuity and connecting people by content).
Image sources: own facebook profile feed and video as listed above. * quote from http://www.reboot.dk/page/1236/en ; cf. [Crumlish et al 2009, p.135-152]
Ambient Intimacy
See Video for Interview with Twitter founder Evan Williams of Obvious http://www.technologyreview.com/video/416292/twitter-and-ambient-intimacy/

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GRAPH THEORY
Modeling Context
Search
Context Detection
Contextual Services
5. Evaluation
Learning Analytics
Offline Evaluation
Resources
Social Patterns
Graph Theory Basics
Re- com- men- der
Human
Resource
User / Learner

45
A Graph G is a pair of sets (Vertexes and Edges) 퐺=(푉,퐸),푉=푥1,…,푥푛,퐸⊆푉2,푉 ∩퐸=∅
Vertexes of a Graph are 푉퐺, Edges are 퐸(퐺)
Number of vertextes 푉=푛=|퐺| is called the order of G
Number of Edges 퐸=푚=퐺
Two vertexes 푥푖,푥푗∈푉(퐺) are adjacent, if 푥푖,푥푗∈퐸퐺. Two edges are adjacent if they have an end in common.
The degree 푑푥=|퐸푥| of 푥 is the number of edges at 푥
A path is a non-empty (sub)graph 푃=(푉,퐸) of the form 푉=푥0,푥1,…,푥푘,퐸={푥0푥1,푥1푥2,…,푥푘−1푥푘} where 푥푖 distinct. 퐸 is the length of P
A tree is a graph where any two vertexes are connected by exactly one unique path Restrictions: This lecture only treats nontrivial, finite graphs and mostly simple graphs, i.e. 퐕>ퟎ,푮 known and <∞ , no loops, no double edges
This and following slides are based on [Diestel2006]
Graphs Defined
푥1
푥2
푥3
푥4
푥5

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Vertexes represent users*
Edges represent relations (friendships) ** Metrics of interest
Which users belong closely to each other?
Which users spread information?
Which users are popular (trendsetting)?
A directed graph (or digraph) 퐷=(푉,퐴) is with V a finite, nonempty set of vertices and A a set of ordered pairs of distinct elements of V called arcs, 퐴={(푥푖,푥푗)} with 푖≠푗,푥푖,푥푗∈푉 meaning directed arcs from 푥푖 to 푥푗
In-degree 푑−푥 of a vertex x is the number of arcs into x. Out-degree equally defined for out-going arcs from x.
Image source: jscreationzs / FreeDigitalPhotos.net ; [[Oellermann, 2013, p.7]
Social Network Graphs
* Could be as well locations, resources, etc.., but is less common
** could be anything else like “exchanged emails”, “have been at the same spot”, “have a goal in common”. It is very usual to define the edges to the needs of your analysis

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Metrics of interest
Which users belong closely to each other?
Which users spread information?
Which users are popular (trendsetting)?
Image source: jscreationzs / FreeDigitalPhotos.net ; [INSNA,2014]
Social Network Graphs
Range (diversity)
Number of links to different others (others are defined as different to the extent that they are not themselves linked to each other, or represent different groups or statuses)
(Tie) strength
Amount of time, emotional intensity, intimacy, and reciprocal services (frequency and multiplexity are also often used as a measure of strength) of a specific link.
Centrality
Extent to which an actor is central to a network. Various measures (including degree, closeness, and betweeness) have been used as indicators of centrality. Some measures of centrality weight an actor's links to others by the centrality of those others.
Closeness
Extent to which an actor is close to, or can easily reach all the other actors in the network. Usually measured by averaging the path distances (direct and indirect links) to all others. A direct link is counted as 1, indirect links receive proportionately less weight (e.g. 1/(number of hops)).
Betweeness
Extent to which an actor mediates, or falls between any other two actors on the shortest path between those actors. Usually averaged across all possible pairs in the network.
Prestige
Based on asymmetric relationships, prestigious actors are the object rather than the source of relations. Measures similar to centrality are calculated by accounting for the direction of the relationship (i.e. in-degree). Prestige can then be defined e.g. as in-degree / out-degree

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Representation
Adjacency matrix
For our finite simple graphs a adjacency matrix is a matrix with zeros on its diagonal and ones (1) for each edge connecting 푥푖 and 푥푗. The matrix is always symmetric if the graph is undirected.
A= 0 10 101 01 100 10 111 11 000 01 00, algorithmically you store an 2-dimensional array A[i][j].
Adjacency list
Storage of all neighbors of the vertexes as a list, e.g.
퐴=푥2,푥4,푥1,푥3,푥4,푥2,푥4,푥5,푥1,푥2,푥3,푥3, algorithmically you store as well a 2-dimensional array
Which way is more efficient?
 Depends on sparsity and operations
(Social Network) Graphs
푥1
푥2
푥3
푥4
푥5

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A graph 푮=(푽,푬) is called n-partite if V admits a partition into r classes such that every edge has its ends in different classes. 2-partite is usually called bipartite.
A hypergraph is a generalization of a graph with 퐸⊆푃푉 ∅
In a k-uniform hypergraph all hyperedges have size k.
Thus an k-uniform k-partite hypergraph consists of edges connecting k-tupels of vertexes that all belong to k disjunct sets.
For hypergraphs see as well http://en.wikipedia.org/wiki/Hypergraph#Bipartite_graph_model
N-partite graphs and k-uniform hypergraphs
푥1
푥2
푥3
푥4
푥5
푥6
푥7
bipartite
3-partite
3-partite
3-uniform
퐻=푉,퐸,
푉=푉푏∩푉푔∩푉푟=푥1,푥2,…,푥7,
퐸={푥1푥4푥6,푥2푥5푥6,푥2푥5푥7,푥3푥4푥7}

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How to weight the edges in an k-uniform, n-partite graph to recommend other related vertexes of a disjunctive set?
How to calculate a betweenness centrality of resources in such n- partite graphs with users, resources and tags?
Emerging aspects
See lectures 8 and 9 on recommender Systems in SLKST context

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Approaches to Modern Web Application Development MVC, ACID, CRUD REST, LAMP, MEAN, PaaS
Social Media Systems Design Aspects
Graph Theory Basics Centrality metrics of (un)directed graphs N-partite, k-uniform hypergraphs
Image sources: http://www.seawaterfoundation.org/siteImages/rivers_art.jpg,, http://vnfa8y5n3zndutm1.zippykid.netdna-cdn.com/wp-content/uploads/2011/12/url7.jpg, http://images.all-free- download.com/images/graphiclarge/s_bahn_71263.jpg, http://de.roblox.com/item.aspx?seoname=U-Bahn&id=28172595, http://faculty.kutztown.edu/rieksts/225/graphs/tripartite_files/image002.jpg,
Summary
Content vs. User
Relationship Types
푥1
푥2
푥3
푥4
푥5
푥6
푥7
Adjacence list 퐴=푥2,푥3,푥1,푥3,푥4,푥2,푥4,푥5,푥1,푥2,푥3,푥3
Ambient Intimacy

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Task1 (2p)
Designing the relation of system design aspects and 3 systems as a graph (connecting social System Design Patterns with Graph Theory) Task 2 (2p) A new (fictive) SLKS system is described
Define and describe 6 types of relationships
How would you implement a reputation/progress system if you have to choose one pattern?
How do you handle content administration? A bonus challenge is included (task 1)
About the Exercise 3

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Learner Models & Profiles
Learning Resources
Data Structures for Learning Content
Metadata to describe Learning Resources
Tags to describe Learning Resources
Next week: Lecture 4 Data Structures for Learner and Resources
Knowledge
Topics
Misconceptions
Learning Styles
Experience
…

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Thank you for your attention, questions, feedback or hints.
Endslide
km-teaching@KOM.tu-da…. .de
km-teaching@KOM.tu-da…. .de

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REST, see JAX-RS specs and https://jersey.java.net/documentation/latest/getting-started.html
Crumlish, C.; Malone, E.: Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User Experience (Animal Guide) (p. 520). Sebastopol, USA: O’Reilly Media, 2009. Letzter Zugriff von http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925
Bell, G.: Building Social Web Applications. Bell, Gavin . Sebastopol: O’Reilly Books, 2009. Letzter Zugriff 29.10.2014 von http://www.amazon.com/Building-Social-Applications-Gavin-Bell/dp/0596518757
Konert, J.; Gerwien, N.; Göbel, S.; Steinmetz, R. Bringing Game Achievements and Community Achievements Together. In Proceedings of the 7th European Conference on Game Based Learning (ECGBL) 2013, pages 319–328, Porto Portugal, 2013. Academic Publishing International. ISBN 978-1- 909507-63-0.
Konert, J.: Interactive Multimedia Learning: Using Social Media for Peer Education in Single-Player Educational Games (p. 220). Darmstadt, Germany: Springer, 2014. Letzter Zugriff von http://www.springer.com/engineering/signals/book/978-3-319-10255-9
Diestel, R.: Graph Theory (Graduate Texts in Mathematics) (3rd ed.). Springer, 2006. Letzter Zugriff 30.10.2014 von http://www.amazon.de/Graph-Theory-Graduate-Texts-Mathematics/dp/3540261834/
Oellermann, O. R.: Topics in Structural Graph Theory. (L. W. Beinecke & R. J. Wilson, Hrsg.). Cambridge, MA, USA: Cambridge University Press, 2013.
INSNA, International Network for Social Network Analysis, 2004. SNA Measures. , p.1. Available at: https://www.socialtext.net/data/workspaces/insna- socnet/attachments/index_of_sna_measures:20041202193540/original/Index of SNA Measures.xls.
Wikipedia, Hypergraphs, Letzer Zugriff 30.10.2014 von http://en.wikipedia.org/wiki/Hypergraph#Bipartite_graph_model
References (order of occurance)

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REST, see JAX-RS specs and https://jersey.java.net/documentation/latest/getting-started.html
Crumlish, C.; Malone, E.: Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User Experience (Animal Guide) (p. 520). Sebastopol, USA: O’Reilly Media, 2009. Letzter Zugriff von http://www.amazon.com/Designing-Social-Interfaces-Principles-Experience/dp/0596154925
Bell, G.: Building Social Web Applications. Bell, Gavin . Sebastopol: O’Reilly Books, 2009. Letzter Zugriff 29.10.2014 von http://www.amazon.com/Building-Social-Applications-Gavin-Bell/dp/0596518757
Diestel, R.: Graph Theory (Graduate Texts in Mathematics) (3rd ed.). Springer, 2006. Letzter Zugriff 30.10.2014 von http://www.amazon.de/Graph-Theory-Graduate-Texts-Mathematics/dp/3540261834/
Further Readings

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Directly named on the corresponding slides
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