ShareIt: Mining      #SocialMedia Activities       for Detecting #EventsRaphaël Troncy <raphael.troncy@eurecom.fr>
Cover of theDecember 25, 2006      issue  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR)...
Quiz Test : who has already ...1. edited a Wikipedia page?2. shared photos on Flickr / Picassa?3. uploaded a video on YouT...
What do you do for getting event info?http://s3mr.eu/agenda/  This official  event page  does a very  poor job to  bring  ...
Looking for more structured information?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR)...
Looking for some media?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turke...
Looking for some media?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turke...
Anything on Flickr / YouTube?Video Lectures reports 1 event and 3 lectures    29/06/2011 -   Lecture at the 2nd Summer Sch...
SSMS participants were better “sharer”  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) -...
Looking for some live information?Not that much ofactivity on Twitter    29/06/2011 -   Lecture at the 2nd Summer School o...
Facebook is the place to be, right?   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - A...
http://www.flickr.com/photos/crsan/3697785107
We have directory of events...   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
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There’s a lot of information out there…   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR)...
http://www.flickr.com/photos/mwparenteau/432039783   26
EventMedia Goals1. Discover PAST, PRESENT and FUTURE events2. Live, relive and predict experiences through shared media3. ...
Agenda A crash course in the world of structured data   #microdata , #microformat , #rdfa   #rdf , #owl , #skos , #spar...
From the Web to the Web of Data                              Fundamental shift:    From sending bits from one host to the ...
From the Web to the Web of Data  BelgianChocolates.com     Pralinés Deluxe Mix  2,99€/100g Shopping Cart  29/06/2011 -   L...
From the Web to the Web of Data            Merchant NameBelgianChocolates.com                                             ...
From the Web to the Web of Data How can website owners help Google make  sense of their bits? Mark up their content usin...
for specific, common, concise datafor custom data, RDF data, multiple schemas
RDFa = a domain-independent way to explicitly embed   your data
RDFa = a domain-independent way to explicitly embed   RDF data
RDFa stands for…    RDF… in HTML … attributes
RDFa in attributes of a web page to…         … transfer data from an application          to another through the web.     ...
weaving RDFain web pages
RDFa step 1    declare the schemas you are using
RDFa step 2   use attributes to mark, type and add data
RDFa step 3  let RDFa agents extract RDF from the document
take this minimal           web page
dont look at the code of this     web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/...
schemas for data in this      web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/...
data seen by users viewing this        web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/200...
data for an RDFa agent in this        web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002...
data shared by both in this      web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/c...
what an RDFa agent knows                    from this     web page#event1 isA cal:Vevent#event1 cal:summary "Weekend off i...
RDF       is the first layer of the SemanticWeb standards 29/06/2011 -   Lecture at the 2nd Summer School on Social Media ...
RDF       stands forResource Description Framework 29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retriev...
RDFis a triple model i.e. every piece of knowledge is broken down into                      ( subject , predicate , object...
image.jpg has for creator Raphael and depictsthe elephant Ganesh   29/06/2011 -   Lecture at the 2nd Summer School on Soci...
image.jpg has for creator Raphaelimage.jpg depicts the elephant Ganesh   29/06/2011 -   Lecture at the 2nd Summer School o...
( image.jpg , creator , Raphael )( image.jpg , depicts , Elephant Ganesh )( subject , predicate , object )   29/06/2011 - ...
in RDF the atoms of knowledge are triples of the form(subject,predicate,object)  29/06/2011 -   Lecture at the 2nd Summer ...
RDF    triples can be seen as arcsof a graph (vertex,edge,vertex)29/06/2011 -   Lecture at the 2nd Summer School on Social...
Raphael          creator                                                image.jpg                                         ...
in RDF resources and properties areidentified by URIs                                                                 http...
in RDF values of properties can also beliterals i.e. strings of characters  29/06/2011 -   Lecture at the 2nd Summer Schoo...
http://www.cwi.nl/~troncy#mehttp://purl.org/dc/elements/1.1#creator                  http://flickr.com/photos/rtroncy/2923...
The RDF Data Model An RDF document is an unordered collection of  statements, each with a subject, predicate and object  ...
Example of RDF Graphs  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey ...
Simple example (Google Vocab)<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Event">   <a href=http://www.exampl...
Rich Snippet Preview  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey  ...
Rich Snippet Preview for Reviews  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antal...
Rich Snippet Preview for People  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Rich Snippet Preview for Recipes  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antal...
Rich Snippet Preview for Events  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Yahoo! Enhanced Results                                                                                                   ...
Yahoo! Vertical Intent Search                          Related actors                           and movies
Snippet generation using metadata Yahoo displays enriched search results for pages that contain  microformat or RDFa mark...
How search engines get this data?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Anta...
Behind the scene With RDFa markup:  <div xmlns:v=http://rdf.data-vocabulary.org/#       typeof="v:Review-aggregate">   <s...
Get your markup with test tool  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya...
How much structured data is out there?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) -...
US/English Rich Snippets UsageSearches onGoogle with                                                                      ...
Worldwide Rich Snippets UsageSearches onGoogle withrich results                                                           ...
RDFa on the rise (Peter Mika@W3C Bilbao)   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR...
Future for Rich Snippets?Even Richer Snippets: Using information form the userssocial graph, given granted access;Direct p...
Future for Rich Snippets?                                                 Fake mock-up. Authors private view.Even Richer S...
Schema.org  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 82
Schema.rdfs.org  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 83
2011/06/27: [Announcement] We have posted an official version of the  schema.org schemas at  http://schema.org/docs/schem...
A lot of Events Categories in Schema.org  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR)...
take away                                  messageLecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Anta...
dont bury  your data in some HTML page
when you publish a page that containsdata…
do make the embeddingexplicit
Linked Data Principles   Tim Berners Lee [2006] (Design Issues)    1. Use URIs to identify things       (anything, not ju...
An Example: DBpedia DBpedia is a community effort to:   extract structured "infobox" information from Wikipedia   inter...
Scraping infobox datahttp://dbpedia.org/resource/Bogotá      29/06/2011 -   Lecture at the 2nd Summer School on Social Med...
Automatic Links Among Open Datasets<http://dbpedia.org/resource/Bogotá>  owl:sameAs <http://sws.geonames.org/3688689/>  ow...
sameAs.org  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 94
Bogotá on Freebase  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   -...
Bogotá on Geonames  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   -...
How Much Linked Data is there ?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Linked Data Cloud – August 2007  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Linked Data Cloud – March 2008  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya...
Linked Data Cloud – September 2008  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Ant...
Linked Data Cloud – March 2009  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya...
Linked Data Cloud – September 2010  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Ant...
The Web of Data Expose open datasets in RDF Set RDF links among the data items for  different datasets Over 26 billion ...
… but let’s STOP counting! Linked Open Numbers  (April 1st 2010) Linked Open Colors  (April 1st 2011)  http://purl.org/c...
Linked data summary URIs, possibly identifying  media fragments                                                          ...
Searching Entities in the Cloud  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Reconciling links in the cloud   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Searching Linked Data  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey ...
Sindice already crawling Schema.org  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - An...
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Browsing Linked Data                                                                                            Tabulator ...
Browsing Linked DataDisco(Free Universityof Berlin)    29/06/2011 -   Lecture at the 2nd Summer School on Social Media Ret...
Browsing LinkedDataMarbles(Free Universityof Berlin)    29/06/2011 -   Lecture at the 2nd Summer School on Social Media Re...
Browsing Linked DataZitgist(Zitgist LLC)     29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3...
Browsing Linked Data                 OpenLink Data Explorer                 (OpenLink Software)  29/06/2011 -    Lecture a...
VisiNav  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 116
Sig.ma  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 117
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TimBL Vision back in 1994  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Tur...
FOAF History (credits: @danbri)                                                                                Web pages  ...
FOAF is a project about sharing information in the Web.                                       Its about ways of describing...
Henry says, “My name is                                                                                ‘Henry Story”      ...
FOAF (Friend-of-a-Friend) FOAF is an ontology for describing people and the  relationships that exist between them Can b...
The FOAF Specification http://xmlns.com/foaf/spec/ (3rd Edition, Jan 2010)    29/06/2011 -   Lecture at the 2nd Summer Sc...
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Integrating SN with FOAF for reuse                                                                           Common format...
Going through the Walled GardensDavid Simonds: Everywhere and nowhere. 19 May 2008, The Economist.     29/06/2011 -   Lect...
FOAF Naut  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 128
FOAF Builder  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 129
FOAF hits the news  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   -...
Relationship Vocabulary http://purl.org/vocab/relationship (Apr 2010)             acquaintance of                  child ...
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Semantically-Interlinked Online Communities A schema for representing users, forums, posts and  threads, containers, and ...
The SIOC ontology http://rdfs.org/sioc/spec/ (March 2010)    29/06/2011 -   Lecture at the 2nd Summer School on Social Me...
Producing SIOC data Over 20 applications for producing SIOC data:   Many are free and open source   Blogs and forums: W...
Portable Data with SIOC and FOAF  29/06/2011 -  136            Lecture at the 2nd Summer School on Social Media Retrieval ...
Collect SIOC from various sources  29/06/2011 -  137            Lecture at the 2nd Summer School on Social Media Retrieval...
Consuming SIOC via Exhibit  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Tu...
Dublin Core http://purl.org/dc/elements/1.1/ (Jan 2008) 15 elements or attribute-value pairs (simple DC)   Contributor,...
Dublin Core example <dc:title>Washing &   ironing clothes.</dc:title> <dc:date>ca. 1942</dc:date> <dc:description>Mexican ...
Good Relations http://purl.org/goodrelations/ (Apr 2010) gr:BusinessEntity for a company or business, gr:LocationOfSale...
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Best Buy                                                       At last yearss SemTech                                     ...
The Open Graph Protocol  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turke...
Open Graph: Getting Started<html xmlns:og="http://opengraphprotocol.org/schema/"  xmlns:fb="http://www.facebook.com/2008/f...
Open Graph Properties The Open Graph protocol defines 5 required properties:    og:title - The title of your object as i...
rNews for the Press RDFa vocabulary for  news articles   Easier to implement than    NewsML   Easier to consume for new...
Wrap up: popular vocabularies  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya,...
Agenda A crash course in the world of structured data   #microdata , #microformat , #rdfa   #rdf , #owl , #skos , #spar...
What are Events? Events are observable occurrences grouping                            People                      Places ...
Ontology: Making an abstraction      What? Where? When? Who?29/06/2011 -                                                  ...
Event-based centric interfaces Action or occurrence taking place at a certain  time at a specific location   Useful for ...
There are already many event ontologies    Event Model                                                              Ontolo...
Fundamental Types of Events Aspect: ongoing activity vs transition between states    cyc:Event ∩ cyc:StaticSituation ≤ c...
Events and Temporal Intervals Relating events to chronological spans of time    Persistent, socially attributed meanings...
Events, Spaces and Places Relating events to places    Semantically significant places    Abstract spatial regions Sup...
Participation in events Object involvement in events:    Simple involvement in event:         abc:Event  abc:involves ...
Events, Influence, Purpose and Causality Making broad assertions linking events to any thing    cidoc:P12.occurred_in_th...
Events, Parts and Composition  As timespan ϵ Bs timespan Event A being part of event B ≠    cidoc:P86.falls_within for e...
Towards a Linked Data Event Model  16/09/2009  29/06/2011 -   Lecture at theAnnotation and Exploration of Media - PetaMedi...
Some mappings in LODE   ABC                         CIDOC                                              DUL                ...
16/09/200929/06/2011 -   Lecture at theAnnotation and Exploration of Media - PetaMedia SYTIM, Lausanne (CH)               ...
Representing Events with  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turk...
EventMedia Goals (User-Centered Design)1. Discover PAST, PRESENT and FUTURE events2. Live, relive and predict experiences ...
1st Collect some opinions…     Online Survey (n=28), 2 group discussions (n=35)Past Experiences(Memorable Events)         ...
EventMedia Project: Questionnaire1. Think about a memorable/recent event you have   participated:   Tell us what it was a...
Brainstorm online with users  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, ...
2nd Look into “real” behaviors… Scenario based study (2 sessions, n=15)                                                  ...
Behavioral Patterns Discovery   Invitations and recommendations   Rely on traditional media   Social networks (faceboo...
Behavioral Patterns Registering and Sharing   Communicating their experience   Pictures and short videos (for sharing) ...
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Behavioral PatternsEVENT                                                                                                  ...
Existing Services Single source with overview (?) Allows opportunistic/serendipitous discovery Limited exploration/brow...
Organize the mess                                                          Event                                          ...
Róisín Murphy at Nouveau Casino                                                                                       E0-0...
Representing Events with  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turk...
Linking the Data  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 177
Reasoning & Annotation Time, Location and Attendance   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Re...
Collaborative Filtering Disambiguate and propagate information about  attendance Identify Interests and provide  Recomme...
Interlinking Linking Agents with    Freebase, Dbpedia, MusicBrainz Linking Venues with    Geonames, Dbpedia, Foursquar...
Interlinking         Event                           Location   Last.fm                           Last.fm   Eventful   ...
SILK Framework Based on the Silk-LSL link specification  language Transformation and algebraic functions: max,  min, avg...
Silk Framework Configuration  SILK - LSL   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR...
Alignement for Agents Alignement base on:    foaf:Agent    rdfs:label                    Eventful           Last.fm    ...
Alignement for Locations                       Eventful         Last.fm              Upcoming                   DBpedia   ...
Alignement for Events Alignement based on title, location and time                                   Eventful            ...
Research challengeshttp://oaei.ontologymatching.org/2011/   29/06/2011 -   Lecture at the 2nd Summer School on Social Medi...
What are Events? Events are observable occurrences grouping                               People                      Plac...
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Róisín Murphy at Nouveau Casino  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Media explicitly associated with the event                  APIs                             Machine tags                 ...
Representing Media with Media Ontology  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) -...
How much data is there?                   Event                    Agent   Location                                       ...
How fast media are uploaded?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, ...
Finding more media that illustrate an eventA. Compute the bounding box area of a venueB. Retrieve all media geo-tagged in ...
A. Bounding box of Nouveau Casino?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Ant...
B. 74 photos taken in this area this day   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR...
C. 85 additional photos with a similar title   29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (...
D. 6 photos after visual pruning                                                                                         ...
How is the visual pruning performed? Model dataset: photo id + photo geo Testing dataset: similar title Low-level featu...
E. 66 photos after uploader heuristics                                                                                    ...
Same process for videos1 video (id)                                                                                       ...
How illustrated are events?                      Query By ID Query By Geo Query By Title Visual Pruning Heuristic  Photos ...
Generating Visual Summaries  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, T...
Generating Visual Summaries  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, T...
Generating Visual Summaries  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, T...
Generating Visual Summaries  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, T...
Generating Visual Summaries  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, T...
Event Detection Detecting events by analyzing user activity on  Flickr (uploading pattern)                               ...
Example: the venue Koko Ground truth obtained by  scraping venue site http://scraperwiki.com/profiles/Hou/    29/06/2011 ...
Example: the venue Melkweg More events detected than  event directories listings Some events have no  illustrative media...
Translating the Ontology and the Data  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - ...
Interface elements                           Facets                            Search Timeline                            ...
Interfaces Perspectives  What: Event/Media Centric  Who: Social Network Visualization  When: Time centric  Where: Loc...
http://www.flickr.com/photos/cocoarmani/1315402174
The Back-end RDF Repository on a web server with:    Sesame2 SPARQL endpoint     with a distributed query engine.    A ...
User Interface  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 217
User Interface  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 218
Agenda A crash course in the world of structured data   #microdata , #microformat , #rdfa   #rdf , #owl , #skos , #spar...
Citizen Sensors in Action                                                                                                 ...
Citizen Journalism                                                                                                Twitter ...
Business Intelligence Trend Spotting,Forecasting, Brand Tracking,Targeted Advertising   Sysomos: Business intelligence b...
What’s in a Tweet?  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   -...
Metadata about People                                                                                                     ...
Metadata about People         User Identification                                                        Interest Metadata...
Metadata about People       Activity Metadata                                                       Influence Metadata    ...
Metadata about Network    Structure Metadata                                                  Relationship Metadata• Commu...
Metadata about Content  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey...
Extracting Entities from Tweets  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antaly...
Twitris: Semantic Social Web Mash-up Facilitates understanding of multi-dimensional social perceptions   over SMS, Tweets,...
Searching on Twitter  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey  ...
Issues with Multiple Keywords Search  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - A...
Let’s try to search with One Keyword  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - A...
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Music Artist                                       Page 60!!tweetNext Saturday @thatsimpsonguy aka Guilty Simpson will be ...
Relation Discovery Framework                    Relation Discovery Framework                                              ...
Entity Extraction and Semantic Enrichment       powered by                                     Julian Assange             ...
Relation Learning Strategies                              entities          time period Relation:                relation...
Where do relationships emerge faster?                                                     Speed of strategies is          ...
On Conferences … we Tweet  29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Tur...
Rich Activity Twitter Event Data  Take Twitter archives from TwapperKeeper  Enrich Tweets with relevant DBPedia   concep...
Find the correspondence                                                                 ?  29/06/2011 -   Lecture at the 2...
meets29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey   - 245
Final Announcement: Google+Gundotra: “We believe online sharing isbroken. And even awkward. We thinkconnecting with other ...
Conclusions The importance of structured data EventMedia   Dataset part of the Semantic Web   LODE used by the UK Arch...
Credits EURECOM: Houda Khrouf, Giuseppe Rizzo CWI: Ryan Shaw, André Fialho, Lynda Hardman Google/Yahoo!: Thomas Steiner...
http://www.slideshare.net/troncy29/06/2011 -   Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya...
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ShareIt: Mining #SocialMedia Activities for Detecting #Events, Talk given at the 2nd Summer School on Social Media Retrieval (S3MR), June 2011, Antalya, Turkey

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ShareIt: Mining SocialMedia Activities for Detecting Events

  1. 1. ShareIt: Mining #SocialMedia Activities for Detecting #EventsRaphaël Troncy <raphael.troncy@eurecom.fr>
  2. 2. Cover of theDecember 25, 2006 issue 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -2
  3. 3. Quiz Test : who has already ...1. edited a Wikipedia page?2. shared photos on Flickr / Picassa?3. uploaded a video on YouTube / Dailymotion?4. used a mobile-aware application: Foursquare / Gowalla?5. published a thought / comment on a blog?6. published its status on Twitter / Identi.ca / FriendFeed?7. shared bookmarks on Del.ico.us / Faviki?8. own a Facebook account and does all this? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -3
  4. 4. What do you do for getting event info?http://s3mr.eu/agenda/ This official event page does a very poor job to bring structured information (Sander Koelstra) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -4
  5. 5. Looking for more structured information? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -5
  6. 6. Looking for some media? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -6
  7. 7. Looking for some media? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -7
  8. 8. Anything on Flickr / YouTube?Video Lectures reports 1 event and 3 lectures 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -8
  9. 9. SSMS participants were better “sharer” 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey -9
  10. 10. Looking for some live information?Not that much ofactivity on Twitter 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 10
  11. 11. Facebook is the place to be, right? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 11
  12. 12. http://www.flickr.com/photos/crsan/3697785107
  13. 13. We have directory of events... 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 13
  14. 14. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 14
  15. 15. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 15
  16. 16. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 16
  17. 17. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 17
  18. 18. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 18
  19. 19. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 19
  20. 20. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 20
  21. 21. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 21
  22. 22. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 22
  23. 23. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 23
  24. 24. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 24
  25. 25. There’s a lot of information out there… 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 25
  26. 26. http://www.flickr.com/photos/mwparenteau/432039783 26
  27. 27. EventMedia Goals1. Discover PAST, PRESENT and FUTURE events2. Live, relive and predict experiences through shared media3. Identify meaningful and/or interesting relationships between events/media/people 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 27
  28. 28. Agenda A crash course in the world of structured data  #microdata , #microformat , #rdfa  #rdf , #owl , #skos , #sparql , #linkeddata EventMedia (User-centered design approach)  LODE: a model for representing events  Scraping and interlinking description of events  Enriching events with illustrating media  Detecting events from social media activities Detecting events from human sensing  #twitter , #foursquare , #facebook 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 28
  29. 29. From the Web to the Web of Data Fundamental shift: From sending bits from one host to the other towards making sense of those bits 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 29
  30. 30. From the Web to the Web of Data BelgianChocolates.com Pralinés Deluxe Mix 2,99€/100g Shopping Cart 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 30
  31. 31. From the Web to the Web of Data Merchant NameBelgianChocolates.com Product Name Pralinés Deluxe Mix2,99€/100g Shopping Cart Product Image Price 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 31
  32. 32. From the Web to the Web of Data How can website owners help Google make sense of their bits? Mark up their content using any of the following syntaxes:  Microdata  Micro format  RDFa "[...] We realized that structured data on the Web can and should accommodate multiple encodings." 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 32
  33. 33. for specific, common, concise datafor custom data, RDF data, multiple schemas
  34. 34. RDFa = a domain-independent way to explicitly embed your data
  35. 35. RDFa = a domain-independent way to explicitly embed RDF data
  36. 36. RDFa stands for… RDF… in HTML … attributes
  37. 37. RDFa in attributes of a web page to… … transfer data from an application to another through the web. … write data only once for web users and web applications.
  38. 38. weaving RDFain web pages
  39. 39. RDFa step 1 declare the schemas you are using
  40. 40. RDFa step 2 use attributes to mark, type and add data
  41. 41. RDFa step 3 let RDFa agents extract RDF from the document
  42. 42. take this minimal web page
  43. 43. dont look at the code of this web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/icaltzd#" xmlns:xs="http://www.w3.org/2001/XMLSchema#" > <body> <p about="#event1" instanceof="cal:Vevent"> <b property="cal:summary">Weekend off in Iona</b>: <span property="cal:dtstart" datatype="xs:date">2006-10-21 </span> to <span property="cal:dtend" datatype="xs:date">2006-10-23 </span>. see <a rel="cal:url" href="http://freetime.example.org/"> Free time web site</a> for info on <span property="cal:location">Iona, UK</span>. </p></body></html>
  44. 44. schemas for data in this web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/icaltzd#" xmlns:xs="http://www.w3.org/2001/XMLSchema#" > <body> <p about="#event1" instanceof="cal:Vevent"> <b property="cal:summary">Weekend off in Iona</b>: <span property="cal:dtstart" datatype="xs:date">2006-10-21 </span> to <span property="cal:dtend" datatype="xs:date">2006-10-23 </span>. see <a rel="cal:url" href="http://freetime.example.org/"> Free time web site</a> for info on <span property="cal:location">Iona, UK</span>. </p></body></html>
  45. 45. data seen by users viewing this web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/icaltzd#" xmlns:xs="http://www.w3.org/2001/XMLSchema#" > <body> <p about="#event1" instanceof="cal:Vevent"> <b property="cal:summary">Weekend off in Iona</b>: <span property="cal:dtstart" datatype="xs:date">2006-10-21 </span> to <span property="cal:dtend" datatype="xs:date">2006-10-23 </span>. see <a rel="cal:url" href="http://freetime.example.org/"> Free time web site</a> for info on <span property="cal:location">Iona, UK</span>. </p></body></html>
  46. 46. data for an RDFa agent in this web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/icaltzd#" xmlns:xs="http://www.w3.org/2001/XMLSchema#" > <body> <p about="#event1" instanceof="cal:Vevent"> <b property="cal:summary">Weekend off in Iona</b>: <span property="cal:dtstart" datatype="xs:date">2006-10-21 </span> to <span property="cal:dtend" datatype="xs:date">2006-10-23 </span>. see <a rel="cal:url" href="http://freetime.example.org/"> Free time web site</a> for info on <span property="cal:location">Iona, UK</span>. </p></body></html>
  47. 47. data shared by both in this web page<html xmlns="http://www.w3.org/1999/xhtml" xmlns:cal="http://www.w3.org/2002/12/cal/icaltzd#" xmlns:xs="http://www.w3.org/2001/XMLSchema#" > <body> <p about="#event1" instanceof="cal:Vevent"> <b property="cal:summary">Weekend off in Iona</b>: <span property="cal:dtstart" datatype="xs:date">2006-10-21 </span> to <span property="cal:dtend" datatype="xs:date">2006-10-23 </span>. see <a rel="cal:url" href="http://freetime.example.org/"> Free time web site</a> for info on <span property="cal:location">Iona, UK</span>. </p></body></html>
  48. 48. what an RDFa agent knows from this web page#event1 isA cal:Vevent#event1 cal:summary "Weekend off in Iona"#event1 cal:dtstart "2006-10-21"^^xs:date#event1 cal:dtend "2006-10-23"^^ xs:date#event1 cal:url <http://freetime.example.org/>#event1 cal:location "Iona, UK"
  49. 49. RDF is the first layer of the SemanticWeb standards 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 50
  50. 50. RDF stands forResource Description Framework 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 51
  51. 51. RDFis a triple model i.e. every piece of knowledge is broken down into ( subject , predicate , object ) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 52
  52. 52. image.jpg has for creator Raphael and depictsthe elephant Ganesh 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 53
  53. 53. image.jpg has for creator Raphaelimage.jpg depicts the elephant Ganesh 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 54
  54. 54. ( image.jpg , creator , Raphael )( image.jpg , depicts , Elephant Ganesh )( subject , predicate , object ) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 55
  55. 55. in RDF the atoms of knowledge are triples of the form(subject,predicate,object) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 56
  56. 56. RDF triples can be seen as arcsof a graph (vertex,edge,vertex)29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 57
  57. 57. Raphael creator image.jpg depicts Ganesh29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 58
  58. 58. in RDF resources and properties areidentified by URIs http://mydomain.org/mypath/myresource 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 59
  59. 59. in RDF values of properties can also beliterals i.e. strings of characters 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 60
  60. 60. http://www.cwi.nl/~troncy#mehttp://purl.org/dc/elements/1.1#creator http://flickr.com/photos/rtroncy/2923/ http://xmlns.com/foaf/0.1#depicts Elephant Ganesh 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 61
  61. 61. The RDF Data Model An RDF document is an unordered collection of statements, each with a subject, predicate and object (aka triples) A triple can be thought of as a labelled arc in a graph Statements describe properties of web resources A resource is any object that can be pointed to by a URI:  a document, a picture, a paragraph on the Web, etc. Properties themselves are also resources (URIs) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 62
  62. 62. Example of RDF Graphs 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 63
  63. 63. Simple example (Google Vocab)<div xmlns:v="http://rdf.data-vocabulary.org/#" typeof="v:Event"> <a href=http://www.example.com/events/poisel_offenback.hmtl rel="v:url" property="v:summary">Philipp Poisel in Offenbach</a> <span property="v:description">See Philipp Poisel in Offenbach</span> When: <span property="v:startDate" content="2011-01-16T19:00- 01:00">Jan 16, 7:00PM</span> <span property="v:endDate" content="2011-01-16T21:00- 01:00">9:00PM</span> Where: <span rel="v:location"><span typeof="v:Organization"> <span property="v:name">Capitol</span>, <span rel="v:address"><span typeof="v:Address"> <span property="v:street-address">Kaiserstrae 106</span>, <span property="v:locality">Offenbach am Main</span>, </span></span> <span rel="v:geo"><span typeof="v:Geo"> <span property="v:latitude" content="50.10945"></span> <span property="v:longitude" content="8.76579" ></span> </span></span> </span></span> Category: <span property="v:eventType">Concert</span></div> 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 64
  64. 64. Rich Snippet Preview 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 65
  65. 65. Rich Snippet Preview for Reviews 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 66
  66. 66. Rich Snippet Preview for People 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 67
  67. 67. Rich Snippet Preview for Recipes 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 68
  68. 68. Rich Snippet Preview for Events 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 69
  69. 69. Yahoo! Enhanced Results Enhanced result with deep links, rating, address. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 70
  70. 70. Yahoo! Vertical Intent Search Related actors and movies
  71. 71. Snippet generation using metadata Yahoo displays enriched search results for pages that contain microformat or RDFa markup using recognized ontologies  Displaying data, images, video  Example: GoodRelations for products  Enhanced results also appear for sites from which we extract information ourselves Also used for generating facets that can be used to restrict search results by object type  Example: “Shopping sites” facet for products Documentation and validator for developers  http://developer.search.yahoo.com Formerly: SearchMonkey allowed developers to customize the result presentation and create new ones for any object type 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 72
  72. 72. How search engines get this data? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 73
  73. 73. Behind the scene With RDFa markup: <div xmlns:v=http://rdf.data-vocabulary.org/# typeof="v:Review-aggregate"> <span rel=“v:itemreviewed"> <h1 property="v:name">Drooling Dog Bar B Q</h1> <img rel="v:rating" src="stars_map.png" alt="4 star rating"/> <em>based on <span property="v:count">15</span> reviews</em></span> </div> With Micro-format markup: <div class="hreview-aggregate"> <span class="item vcard"> <h1 class="fn org">Drooling Dog Bar B Q</h1> <img class="rating average" src= "stars_map.png" alt="4 star rating" /> <em>based on <span class="count">15</span> reviews</em></span> </div> 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 74
  74. 74. Get your markup with test tool 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 75
  75. 75. How much structured data is out there? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 76
  76. 76. US/English Rich Snippets UsageSearches onGoogle with 2x sincerich results Oct 2009 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 77
  77. 77. Worldwide Rich Snippets UsageSearches onGoogle withrich results 4x since Oct 2009 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 78
  78. 78. RDFa on the rise (Peter Mika@W3C Bilbao) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 79
  79. 79. Future for Rich Snippets?Even Richer Snippets: Using information form the userssocial graph, given granted access;Direct price comparison. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 80
  80. 80. Future for Rich Snippets? Fake mock-up. Authors private view.Even Richer Snippets using multimedia semantics. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 81
  81. 81. Schema.org 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 82
  82. 82. Schema.rdfs.org 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 83
  83. 83. 2011/06/27: [Announcement] We have posted an official version of the schema.org schemas at http://schema.org/docs/schemaorg.owl “This allows the schema.org schemas to be used with all OWL-aware tools such as editors, validators etc., as well as to create mappings to other Semantic Web schemas. We would like to acknowledge the Linked Data Research Center at DERI, in particular Michael Hausenblas and Richard Cyganiak, for their work on schemas.rdfs.org, and for their help in developing the OWL schema for schema.org.” 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 84
  84. 84. A lot of Events Categories in Schema.org 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 85
  85. 85. take away messageLecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, 86
  86. 86. dont bury your data in some HTML page
  87. 87. when you publish a page that containsdata…
  88. 88. do make the embeddingexplicit
  89. 89. Linked Data Principles Tim Berners Lee [2006] (Design Issues) 1. Use URIs to identify things (anything, not just documents); 2. Use HTTP URIs – globally unique names, distributed ownership – so that people can look up those names; 3. Provide useful information in RDF – when someone looks up a URI; 4. Include RDF links to other URIs – to enable discovery of related information 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 90
  90. 90. An Example: DBpedia DBpedia is a community effort to:  extract structured "infobox" information from Wikipedia  interlink DBpedia with other datasets on the Web 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 91
  91. 91. Scraping infobox datahttp://dbpedia.org/resource/Bogotá 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 92
  92. 92. Automatic Links Among Open Datasets<http://dbpedia.org/resource/Bogotá> owl:sameAs <http://sws.geonames.org/3688689/> owl:sameAs<http://rdf.freebase.com/ns/guid.9202a8c04000641f DBpedia8000000000167bab> dbpedia:population "6776009" ... <http://sws.geonames.org/3688689/> owl:sameAs <http://dbpedia.org/resource/Bogotá> wgs84_pos:lat "4.6"Geonames wgs84_pos:long "-74.0833333" geo:population "7102602" ... 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 93
  93. 93. sameAs.org 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 94
  94. 94. Bogotá on Freebase 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 95
  95. 95. Bogotá on Geonames 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 96
  96. 96. How Much Linked Data is there ? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 97
  97. 97. Linked Data Cloud – August 2007 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 98
  98. 98. Linked Data Cloud – March 2008 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 99
  99. 99. Linked Data Cloud – September 2008 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 100
  100. 100. Linked Data Cloud – March 2009 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 101
  101. 101. Linked Data Cloud – September 2010 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 102
  102. 102. The Web of Data Expose open datasets in RDF Set RDF links among the data items for different datasets Over 26 billion triples, 500 millions links, 203 datasets (September 2010) ... still counting 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 103
  103. 103. … but let’s STOP counting! Linked Open Numbers (April 1st 2010) Linked Open Colors (April 1st 2011) http://purl.org/colors/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 104
  104. 104. Linked data summary URIs, possibly identifying media fragments wp:2006_FIFA_World_Cup#Final + annotations (tags) events:id + links among fragments & annotationsgeonames:2950159 nar:subject nar:location nc:15054000 foaf:depicts dbpedia:Zidane 105 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 105
  105. 105. Searching Entities in the Cloud 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 106
  106. 106. Reconciling links in the cloud 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 107
  107. 107. Searching Linked Data 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 108
  108. 108. Sindice already crawling Schema.org 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 109
  109. 109. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 110
  110. 110. Browsing Linked Data Tabulator (CSAIL, MIT) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 111
  111. 111. Browsing Linked DataDisco(Free Universityof Berlin) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 112
  112. 112. Browsing LinkedDataMarbles(Free Universityof Berlin) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 113
  113. 113. Browsing Linked DataZitgist(Zitgist LLC) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 114
  114. 114. Browsing Linked Data OpenLink Data Explorer (OpenLink Software) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 115
  115. 115. VisiNav 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 116
  116. 116. Sig.ma 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 117
  117. 117. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 118
  118. 118. TimBL Vision back in 1994 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 119
  119. 119. FOAF History (credits: @danbri) Web pages describe the World Each makes ‘claims’ They can disagree 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 120
  120. 120. FOAF is a project about sharing information in the Web. Its about ways of describing things using computers, so that those descriptions can be linked together, mixed up with other data, and searched.Friend of a FriendPeople, groups, accounts, photos, IM, life on the Web.Machine-readable pages, de-centralised, freely extensible. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 121
  121. 121. Henry says, “My name is ‘Henry Story” Joe says, “I know Henry who knows Jane”Joe knows someonecalled “Henry Story” 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 122
  122. 122. FOAF (Friend-of-a-Friend) FOAF is an ontology for describing people and the relationships that exist between them Can be integrated with any other SW vocabularies Some services with FOAF exports: People can also create their own FOAF document and link to it from their homepage FOAF documents usually contain personal info, links to friends, and other related resources 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 123
  123. 123. The FOAF Specification http://xmlns.com/foaf/spec/ (3rd Edition, Jan 2010) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 124
  124. 124. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 125
  125. 125. Integrating SN with FOAF for reuse Common formats, unique URIs* Source: Sheila Kinsella, Applications of Social Network Analysis 2007 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 126
  126. 126. Going through the Walled GardensDavid Simonds: Everywhere and nowhere. 19 May 2008, The Economist. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 127
  127. 127. FOAF Naut 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 128
  128. 128. FOAF Builder 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 129
  129. 129. FOAF hits the news 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 130
  130. 130. Relationship Vocabulary http://purl.org/vocab/relationship (Apr 2010) acquaintance of child of collaborates with lost contact with ambivalent of apprentice to close friend of colleague of employed by ancestor of enemy of has met influenced by knows by reputation grandchild of knows in passing lives with mentor of neighbor of parent ofparticipant relationship sibling of spouse of works with would like to now 35 new properties to complement FOAF 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 131
  131. 131. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 132
  132. 132. Semantically-Interlinked Online Communities A schema for representing users, forums, posts and threads, containers, and other items in online community sites, for reuse and interoperability:  Aims to fully describe the structure of content in these sites  Also to create new connections between forums and posts from different types of discussion systems (blogs, forums, mailing lists, etc.) and content items / containers on Web 2.0 sites  And to browse connected posts and channels in interesting ways (e.g. distributed linked conversations, decentralised discussion channels and communities, etc.) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 133
  133. 133. The SIOC ontology http://rdfs.org/sioc/spec/ (March 2010) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 134
  134. 134. Producing SIOC data Over 20 applications for producing SIOC data:  Many are free and open source  Blogs and forums: WordPress, phpBB, Drupal, b2evolution  “Legacy” applications: mailing lists, IRC  New media: Twitter, Jaiku, Facebook, Flickr APIs for those who may wish to make their own producers:  PHP, Perl, Java, Ruby on Rails 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 135
  135. 135. Portable Data with SIOC and FOAF 29/06/2011 - 136 Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey
  136. 136. Collect SIOC from various sources 29/06/2011 - 137 Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey
  137. 137. Consuming SIOC via Exhibit 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 138
  138. 138. Dublin Core http://purl.org/dc/elements/1.1/ (Jan 2008) 15 elements or attribute-value pairs (simple DC)  Contributor, Coverage, Creator, Date, Description, Format, Identifier, Language, Publisher, Relation, Rights, Source, Subject, Title, Type 55 elements or attribute-value pairs (qualified DC)  http://purl.org/dc/terms/  http://purl.org/dc/dcmitype/  http://purl.org/dc/dcam/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 139
  139. 139. Dublin Core example <dc:title>Washing & ironing clothes.</dc:title> <dc:date>ca. 1942</dc:date> <dc:description>Mexican workers washing and ironing clothes.</dc:description> <dc:subject> Agricultural laborers--Mexican--Oregon; Agricultural laborers--Housing--Oregon; Laundry </dc:subject> <dc:type>Image</dc:type> <dc:source>Silver gelatin prints</dc:source> <dc:rights> Permission to use must be obtained from OSU Archives.</dc:rights> <dc:identifier>P20:1069</dc:identifier> <dc:identifier>http://digitalcollections.library.oreg onstate.edu/u?/bracero,37</dc:identifier> 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 140
  140. 140. Good Relations http://purl.org/goodrelations/ (Apr 2010) gr:BusinessEntity for a company or business, gr:LocationOfSalesOrServiceProvisioning for a store, gr:ProductOrServicesSomeInstancesPlaceholder for products or services (if there are multiple items), gr:ActualProductOrServiceInstance for a particular product or service (e.g. used items), gr:ProductOrServiceModel for the datasheet describing the features of a product, and gr:Offering for an offer to sell, repair, lease something, or to express interest in such an offer. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 141
  141. 141. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 142
  142. 142. Best Buy At last yearss SemTech conference, Myers said that it had resulted in a 30% increase in search traffic. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 143
  143. 143. The Open Graph Protocol 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 144
  144. 144. Open Graph: Getting Started<html xmlns:og="http://opengraphprotocol.org/schema/" xmlns:fb="http://www.facebook.com/2008/fbml"> <head> <title>The Rock (1996)</title> <meta property="og:title" content="The Rock"/> <meta property="og:type" content="movie"/> <meta property="og:url“ content="http://www.imdb.com/title/tt0117500/"/> <meta property="og:image" content="http://ia.media- imdb.com/rock.jpg"/> ... </head> ... </html> 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 145
  145. 145. Open Graph Properties The Open Graph protocol defines 5 required properties:  og:title - The title of your object as it should appear within the graph, e.g., "The Rock".  og:type - The type of your object, e.g., "movie". See also http://developers.facebook.com/docs/opengraph#types  og:image - An image URL which should represent your object within the graph. The image must be at least 50px by 50px and have a maximum aspect ratio of 3:1.  og:url - The canonical URL of your object that will be used as its permanent ID in the graph, e.g., http://www.imdb.com/title/tt0117500/  og:site_name - A human-readable name for your site, e.g., "IMDb“ Optional properties  og:description - A one to two sentence description of your page.*  + location (7 properties) + contact (3 properties) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 146
  146. 146. rNews for the Press RDFa vocabulary for news articles  Easier to implement than NewsML  Easier to consume for news search and other readers, aggregators Under development at the IPTC  March: v0.1 approved  Final version by Sept 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 147
  147. 147. Wrap up: popular vocabularies 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 148
  148. 148. Agenda A crash course in the world of structured data  #microdata , #microformat , #rdfa  #rdf , #owl , #skos , #sparql , #linkeddata EventMedia (User-centered design approach)  LODE: a model for representing events  Scraping and interlinking description of events  Enriching events with illustrating media  Detecting events from social media activities Detecting events from human sensing  #twitter , #foursquare , #facebook 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 149
  149. 149. What are Events? Events are observable occurrences grouping People Places Time 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 150
  150. 150. Ontology: Making an abstraction What? Where? When? Who?29/06/2011 - http://www.flickr.com/photos/benheine/4732941129 Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 151
  151. 151. Event-based centric interfaces Action or occurrence taking place at a certain time at a specific location  Useful for organizing and browsing collections of media  Useful for discovering complex relationships between data  Need for an expressive event model for connecting pieces of data  Not Yet Another Model! 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 152
  152. 152. There are already many event ontologies Event Model Ontology URLCIDOC CRM http://cidoc.ics.forth.gr/OWL/cidoc_v4.2.owlABC Ontology http://metadata.net/harmony/ABC/ABC.owlEvent Ontology http://purl.org/NET/c4dm/event.owl#EventsML-G2 http://www.iptc.org/EventsML/Dolce+DnS Ultralite http://www.loa-cnr.it/ontologies/DUL.owlF http://events.semantic- multimedia.org/ontology/2008/12/15/model.owlOpenCyc Ontology http://www.opencyc.org/SEM http://semanticweb.cs.vu.nl/2009/04/event/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 153
  153. 153. Fundamental Types of Events Aspect: ongoing activity vs transition between states  cyc:Event ∩ cyc:StaticSituation ≤ cyc:Situation  cidoc:E5.Event ∩ cidoc:E3.Condition_State ≤ cidco:E2.Temporal_Entity  abc:Event is a transition between abc:Situation ≈ cidoc:E3.Condition_State Agentivity: who has produced the event?  cyc:Action, dul:Action ≤ Event  E7.Activity ≤ E5.Event  abc:Action ∩ abc:Event = Ø Events are fully described as a set of actions taken by specific agents Issue for modeling e.g. earthquakes Interpretation matters!  Identifiable changes or not? Agency can be assigned?  dul:Situation describe dul:Event  dul:Action, dul:Process ≤ dul:Event 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 154
  154. 154. Events and Temporal Intervals Relating events to chronological spans of time  Persistent, socially attributed meanings  Arbitrary system for subdividing an abstract space Modeling a class for temporal intervals and use an OP  ABC, CIDOC, EO (owl:TemporalEntity) Modeling a XML Schema typed value and use a DP  Pro: simplicity, values expressed as xsd:date or xsd:dateTime  Cons: inability to express uncertain period or when there is no coincidence with date units Having two properties  dul:hasEventDate ... litteral value  dul:isObservableAt ... dul:TimeInterval 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 155
  155. 155. Events, Spaces and Places Relating events to places  Semantically significant places  Abstract spatial regions Support spatial regions only: ABC, CIDOC, EO  eo:Event  eo:place  wgs84:SpatialThing  cidoc:E5.Event  cidoc:P7.took_place_at  cidoc:E53.Place Support the place/space distinction  dul:Event  dul:hasLocation  dul:Place  dul:Event  dul:hasRegion  dul:SpaceRegion  Most flexible approach: allow to resolve to places with no geographical coordinate systems (e.g. mythical events, SecondLife) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 156
  156. 156. Participation in events Object involvement in events:  Simple involvement in event: abc:Event  abc:involves  owl:Thing (≤ abc:Actuality) cidoc:E5.Event  cidoc:P12.occurred_in_the_presence_of  cidoc:E77 dul:Event  dul:hasParticipant  dul:Object eo:Event  eo:factor  owl:Thing  Tangible thing which results from an event: abc:Event  abc:hasResult  owl:Thing eo:Event  eo:product  owl:Thing Agent participation in events:  abc:hasParticipant ≤ abc:hasPresence  cidoc:P11.had_participant ≤ cidoc:P14.carried_out_by  dul:involvesAgent ≤ abc:hasParticipant 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 157
  157. 157. Events, Influence, Purpose and Causality Making broad assertions linking events to any thing  cidoc:P12.occurred_in_the_presence_of, cidoc:P15.was_influenced_by  eo:factor, abc:hasResult F model uses the DnS pattern 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 158
  158. 158. Events, Parts and Composition As timespan ϵ Bs timespan Event A being part of event B ≠  cidoc:P86.falls_within for expressing containment among timespans  cidoc:P9.consist_of ≈ eo:sub_event ≈ abc:isSubEventOf Linking sub-events with parthood  dul:hasPart The 20th century contains the year 1923 World War II included Pearl Harbour Linking sub-events with composition  dul:hasConstituent The French revolution is composed of the Bastille catch 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 159
  159. 159. Towards a Linked Data Event Model 16/09/2009 29/06/2011 - Lecture at theAnnotation and Exploration of Media - PetaMedia SYTIM, Lausanne (CH) Event-based 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 160
  160. 160. Some mappings in LODE ABC CIDOC DUL EO LODEatTime P4.has_time_span isObservableAt time atTime P7.took_place_at place inSpaceinPlace hasLocation atPlaceinvolves P12.occurred_in_the_ hasParticipant factor involved presence_ofhasPresence P11.had_participant involvesAgent agent involvedAgent 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 161
  161. 161. 16/09/200929/06/2011 - Lecture at theAnnotation and Exploration of Media - PetaMedia SYTIM, Lausanne (CH) Event-based 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 162
  162. 162. Representing Events with 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 163
  163. 163. EventMedia Goals (User-Centered Design)1. Discover PAST, PRESENT and FUTURE events2. Live, relive and predict experiences through shared media3. Identify meaningful and/or interesting relationships between events/media/people 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 164
  164. 164. 1st Collect some opinions… Online Survey (n=28), 2 group discussions (n=35)Past Experiences(Memorable Events) Existing Technologies• Discovery • Opinions Scenarios• Decision making • Interests Requirements• Registering & sharing • Suggestions 1st Design Concept• Meaningful relationships • Benefits/drawbacks 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 165
  165. 165. EventMedia Project: Questionnaire1. Think about a memorable/recent event you have participated:  Tell us what it was and what type of event was it2. How do you usually find out or look for such events?3. What is important to support your decision about going to an event?4. Once you attended to an event, how do you register the moment and share your experience?5. What could be considered meaningful (surprising or entertaining) relationships among events? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 166
  166. 166. Brainstorm online with users 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 167
  167. 167. 2nd Look into “real” behaviors… Scenario based study (2 sessions, n=15) Opinions Scenarios Reenact 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 168
  168. 168. Behavioral Patterns Discovery  Invitations and recommendations  Rely on traditional media  Social networks (facebook - students)  Previously attended events or venues Decision Making  Who’s Joining?  Where, When, How Much? (constraints)  What? (e.g. type, performer, topic)  Subjective factors (fun, atmosphere) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 169
  169. 169. Behavioral Patterns Registering and Sharing  Communicating their experience  Pictures and short videos (for sharing)  Media directories and social networks Meaningful Relationships  Similar categories, attributes and content  User attendance (similar interests, behaviors)  Repeated events (e.g. annual festivals) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 170
  170. 170. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey 171
  171. 171. Behavioral PatternsEVENT EVENT EVENT 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 172
  172. 172. Existing Services Single source with overview (?) Allows opportunistic/serendipitous discovery Limited exploration/browsing features Information overload (cluttered, difficult) Information incompleteness (coverage, decision) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 173
  173. 173. Organize the mess Event Media Scrape event directories Link the information Find media illustrating events Design the application Interface Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. http://lod-cloud.net/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 174
  174. 174. Róisín Murphy at Nouveau Casino E0-001-005971169-9 350591 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 175
  175. 175. Representing Events with 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 176
  176. 176. Linking the Data 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 177
  177. 177. Reasoning & Annotation Time, Location and Attendance 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 178
  178. 178. Collaborative Filtering Disambiguate and propagate information about attendance Identify Interests and provide Recommendations 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 179
  179. 179. Interlinking Linking Agents with  Freebase, Dbpedia, MusicBrainz Linking Venues with  Geonames, Dbpedia, Foursquare (via Uberblic) Linking Events with  Last.fm, Upcoming, Eventful Linking Categories with  Facebook, Eventful, Upcoming, Zevents, LinkedIn,Eventbrite, TicketMaster Linking Users with  Social Graph API 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 180
  180. 180. Interlinking Event Location Last.fm  Last.fm Eventful  Eventful Upcoming  Upcoming DBpedia  DBpedia Freebase  Freebase Uberblic MusicBrainz Uberblic  Foursquare Agent  Geonames Last.fm Event Eventful Media MusicBrainz Foursquare DBpedia DBpedia Freebase Geonames Freebase Uberblic New York Times 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 181
  181. 181. SILK Framework Based on the Silk-LSL link specification language Transformation and algebraic functions: max, min, avg, etc. Several metrics available:  Syntax: equality, Jaro, Leveinstein, n-gram  Lexical: WordNet  Geo: wgs84  Temporal: date 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 182
  182. 182. Silk Framework Configuration SILK - LSL 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 183
  183. 183. Alignement for Agents Alignement base on:  foaf:Agent  rdfs:label Eventful Last.fm MusicBrainz Dbpedia Uberblic NYTimes (6543) (50151) (459023) (107112) (236691) (4794) Eventful - 2865 (44%) 3616 (55%) 1985 (30%) 1567 (24%) 7 (0.1%) Last.fm 2865 (6%) - 26619 (53%) 9442 (19%) 12905 (26%) 14 (0.03%) Examples :  Donavan Frankenreiter / Donovan Frankenreiter (Jaro 0.98) × Birds & Batteries / Birds and Batteries (Jaro 0.70) Total :  Eventful : 61 %  Last.fm : 58 % 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 184
  184. 184. Alignement for Locations Eventful Last.fm Upcoming DBpedia Foursquare Geonames (13516) (15857) (5173) (496728) (641770) (1090357) Eventful - 998 (7%) 366 (3%) 90 (0,7%) 1296 (10%) 320 (2%) Last.fm 998 (6%) - 626 (4%) 141 (0.9%) 911 (6%) 345 (2%) Upcoming 366 (7%) 626 (12%) - 74 (1,4%) 1300 (25%) 232 (4%) Examples :  The Stone Bar (34.1019 ;-118.304) Dist : 29 m – Score (sim): 0.98  The Stone (34.1017 ;-118.304) × fall harvest wine dinner bavarian inn restaurant frankenmuth (43.32 ; -83.73) Dist : 80 m × Frankenmuth Bavarian Inn Restaurant (43.32 ; -83.74) Score : 0.92 Total :  Eventful : 17 %  Last.fm : 15 %  Upcoming : 36 % 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 185
  185. 185. Alignement for Events Alignement based on title, location and time Eventful Last.fm Upcoming DBpedia Uberblic Music Festival Performer (37647) (57258) (13114) (662) (228238) Eventful - 76 (0,2%) 34 (0,1%) 28 (0,1%) 15 (0,04%) Last.fm 76 (0,1%) - 586 (1%) 389 (0,7%) 1148 (2%) Upcoming 34 (0,3%) 586 (4%) - 31 (0,2%) 15 (0,1%) Example :  LastFm : « Camp Bestival » à « Lulworth Castle » le 18/07/2008  Eventful : « New Camp Bestival Dorset » à « Lulworth Castle » le 18/07/2008 Total :  Eventful : 0,4 %  Last.fm : 3;8 %  Upcoming : 4,8 % 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 186
  186. 186. Research challengeshttp://oaei.ontologymatching.org/2011/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 187
  187. 187. What are Events? Events are observable occurrences grouping People Places Time Experiences documented by Media 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 188
  188. 188. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 189
  189. 189. Róisín Murphy at Nouveau Casino 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 190
  190. 190. Media explicitly associated with the event APIs Machine tags “lastfm:events” 4790 photos, 263 1.7 million images over videos over 110 events 108.000 events 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 191
  191. 191. Representing Media with Media Ontology 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 192
  192. 192. How much data is there? Event Agent Location Photos UserLast.fm 57,258 50,150 16,471 1,425,318 18,542Upcoming 13,114 0 7,330 347,959 4,518Eventful 37,647 6,543 14,576 0 0Total 108,019 56,693 38,377 1,773,277 23,060 1,248,021 geo-tagged photos by propagating information from events! 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 193
  193. 193. How fast media are uploaded? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 194
  194. 194. Finding more media that illustrate an eventA. Compute the bounding box area of a venueB. Retrieve all media geo-tagged in this areaC. Retrieve all media with a similar titleD. Prune the results with visual analysisE. Extend the result set with all media from the same uploader 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 195
  195. 195. A. Bounding box of Nouveau Casino? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 196
  196. 196. B. 74 photos taken in this area this day 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 197
  197. 197. C. 85 additional photos with a similar title 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 198
  198. 198. D. 6 photos after visual pruning        29/06/2011 -  Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 199 
  199. 199. How is the visual pruning performed? Model dataset: photo id + photo geo Testing dataset: similar title Low-level features used:  Color moments, Gabor texture, Edge histogram L1 distance on the K-nearest neighbors Threshold  Min L1 distance between two model image pairs  Conservative approach 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 200
  200. 200. E. 66 photos after uploader heuristics  hellerpop DustGraph / Stefan cartoixa 13 photos 46 photos 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 201
  201. 201. Same process for videos1 video (id) 3 videos (geo)26 videos (title) Visual pruning performed on key frames   Nb positive > 50% 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 202
  202. 202. How illustrated are events? Query By ID Query By Geo Query By Title Visual Pruning Heuristic Photos 5 74 (74) 85 (85) 6 (6) 66 (66) Videos 1 3 (0) 23 (0) 13 (0) - (title) Videos 10 (10)(title+venue)  20 events  Model dataset: 785 photos  Testing dataset: 1766 photos (1573 positive, 193 negative)  Results: 439 photos (99% precision, 28% recall) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 203
  203. 203. Generating Visual Summaries 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 204
  204. 204. Generating Visual Summaries 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 205
  205. 205. Generating Visual Summaries 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 206
  206. 206. Generating Visual Summaries 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 207
  207. 207. Generating Visual Summaries 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 208
  208. 208. Event Detection Detecting events by analyzing user activity on Flickr (uploading pattern) Accumulated Number of Uploading Photos 1400 1200 Possible Event 1000 800 600 400 200 0 Time 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 209
  209. 209. Example: the venue Koko Ground truth obtained by scraping venue site http://scraperwiki.com/profiles/Hou/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 210
  210. 210. Example: the venue Melkweg More events detected than event directories listings Some events have no illustrative media 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 211
  211. 211. Translating the Ontology and the Data 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 212
  212. 212. Interface elements Facets Search Timeline Events Media Attendance ME Content and Background Location (Map) Actions Sorting29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 213
  213. 213. Interfaces Perspectives What: Event/Media Centric Who: Social Network Visualization When: Time centric Where: Location Centric 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 214
  214. 214. http://www.flickr.com/photos/cocoarmani/1315402174
  215. 215. The Back-end RDF Repository on a web server with:  Sesame2 SPARQL endpoint with a distributed query engine.  A RESTful API that provides different methods and JSON representations of resources available in the dataset. RDF JSON 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 216
  216. 216. User Interface 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 217
  217. 217. User Interface 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 218
  218. 218. Agenda A crash course in the world of structured data  #microdata , #microformat , #rdfa  #rdf , #owl , #skos , #sparql , #linkeddata EventMedia (User-centered design approach)  LODE: a model for representing events  Scraping and interlinking description of events  Enriching events with illustrating media  Detecting events from social media activities Detecting events from human sensing  #twitter , #foursquare , #facebook 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 219
  219. 219. Citizen Sensors in Action  Mumbai Terror Attack  Iran Election 2009  Haiti Earthquake 2010  US Healthcare Debate 2009 http://huff.to/hp0OhA 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 220
  220. 220. Citizen Journalism Twitter Journalism Images: http://bit.ly/9GVfPQ, http://bit.ly/hmrTYV 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 221
  221. 221. Business Intelligence Trend Spotting,Forecasting, Brand Tracking,Targeted Advertising  Sysomos: Business intelligence by engaging, measuring and understanding activities in Social Media  Trendspotting: Detecting, analyzing and evaluating trends for business.  Simplify: A collaborative platform to monitor, measure and engage customers using Social Media.  Shoutlet: Managing social media marketing communication using a single platform.  Reputation.com: Preserves privacy and defends reputation by protecting attacks on personal information. 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 222
  222. 222. What’s in a Tweet? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 223
  223. 223. Metadata about People Identification Interests Activity Network 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 224
  224. 224. Metadata about People User Identification Interest Metadata Metadata • Author type• User-id - Trustee/donor, journalist, blogger, scientist etc.• Screen/Display-name of user• Real name of user • Favorite tweets• Location • Types of lists subscribed• Profile Creation Date • Style of Writing (personality• User description indicator) - Biodata of the user • No. of Followees - Link to webpage of the user • Majority of author type of Followees 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 225
  225. 225. Metadata about People Activity Metadata Influence Metadata (Inferring People Metadata from Network level Information)• Age of the profile • No. of Followers – normal, influential• Frequency of posts • No. of Mentions• Timestamp of last status • No. of Retweets/Forwards• No. of Posts • No. of Replies• No. of Lists/groups created • No. of Lists/groups following• No. of Lists/groups subscribed • No. of people following back • Authority & Hub ScoresWeb Presence: - User affiliations - KLOUT Score – influence measure (http://www.klout.com) 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 226
  226. 226. Metadata about Network Structure Metadata Relationship Metadata• Community Size • Type of Relationship• Community growth rate • Relationship strength• Largest Strongly Connected • User Homophily (based onComponent size certain characteristic such as• Weakly Connected Components location, interest etc.)& Max(WCC) size • Reciprocity: mutual relationship• Average Degree of Separation • Active Community/ Ties• Clustering Coefficient 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 227
  227. 227. Metadata about Content 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 228
  228. 228. Extracting Entities from Tweets 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 229
  229. 229. Twitris: Semantic Social Web Mash-up Facilitates understanding of multi-dimensional social perceptions over SMS, Tweets, multimedia Web content, electronic news mediaAmit Sheth, http://twitris.knoesis.org/ 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 230
  230. 230. Searching on Twitter 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 231
  231. 231. Issues with Multiple Keywords Search 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 232
  232. 232. Let’s try to search with One Keyword 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 233
  233. 233. Page 1
  234. 234. Page 2
  235. 235. Page 3
  236. 236. Music Artist Page 60!!tweetNext Saturday @thatsimpsonguy aka Guilty Simpson will be performing at I was looking for in my hometwon Eindhoven. #realliveshit #iwillspinrecords Area51 about 9 hours ago via BlackberryLocations
  237. 237. Relation Discovery Framework Relation Discovery Framework temporal relation constraints type typed relations microblog posts Entity Person A Location A Person A Location A isLocatedIn extraction & Location B Relation semantic Group A discovery Person A Group A news articles enrichment involvedIn Event A weighting source scheme selection Applications - Browsing support - Query suggestions - Schema enrichmentIlknur Celik, Fabian Abel, Geert-Jan HoubenWeb Information Systems, TU Delft
  238. 238. Entity Extraction and Semantic Enrichment powered by Julian Assange @bob: Julian Assange got Tweet-based arrested enrichmentJulian Assange Julian Assange News-basedLondon arrested enrichment Julian Assange, the founder of WikiLeaks, is under arrest in London…WikiLeaks
  239. 239. Relation Learning Strategies entities time period Relation: relation(e1, e2, type, tstart, tend, weight) type/label of relation relatedness Relation Learning strategy:  Input: entity e1 and e2, time period (tstart, tend)  Challenge: infer weight and type of the relation for the given Weighting according to co-occurrence frequency:  Tweet-based: count co-occurrence in tweets  News-based: count co-occurrence in news  Tweet-News-based: count co-occurrence in both tweets and news
  240. 240. Where do relationships emerge faster? Speed of strategies is domain-dependent time difference (in days) of first occurrence of relationship News is faster Twitter is fasterhttp://wis.ewi.tudelft.nl/icwe2011/relation-learning/
  241. 241. On Conferences … we Tweet 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 242
  242. 242. Rich Activity Twitter Event Data  Take Twitter archives from TwapperKeeper  Enrich Tweets with relevant DBPedia concepts using Zemanta  Rely on existing Linked Data about talks to perform the mappings.Milan Stankovic & Mattew Rowe:Mapping Tweets to Conference Talks, SDOW 2010 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 243
  243. 243. Find the correspondence ? 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 244
  244. 244. meets29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 245
  245. 245. Final Announcement: Google+Gundotra: “We believe online sharing isbroken. And even awkward. We thinkconnecting with other people is a basichuman need. We do it all the time in reallife, but our online tools are rigid. Theyforce us into buckets — or into beingcompletely public” 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 246
  246. 246. Conclusions The importance of structured data EventMedia  Dataset part of the Semantic Web  LODE used by the UK Archives Hub  Method for finding media illustrating scheduled events  Method for detecting events from social media  Social Event Detection Task Event-based approach for users to explore, annotate and share media  UX can help semantics, semantics can help UX  Outstanding challenges in interlinking and curating the data 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 247
  247. 247. Credits EURECOM: Houda Khrouf, Giuseppe Rizzo CWI: Ryan Shaw, André Fialho, Lynda Hardman Google/Yahoo!: Thomas Steiner, Peter Mika Colleagues: Fabien Gandon, Alexandre Passant, Amit Sheth, Fabian Abel, Milan Stankovic, Matthew Rowe … and the “media sharers” 29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 248
  248. 248. http://www.slideshare.net/troncy29/06/2011 - Lecture at the 2nd Summer School on Social Media Retrieval (S3MR) - Antalya, Turkey - 249

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