Live Social Semantics

Martin Szomszor - City eHealth Research Centre, UK

Ciro Cattuto - ISI Foundation, Turin, ItalyWouter Van den Broeck - ISI Foundation, Turin, Italy

Alain Barrat - Centre de Physique Théorique, Marseille, FranceHarith Alani - Knowledge Media Institute, The Open University, UK

A novel application that integrates data from the semantic web, online social networks, and a real-

world face-to-face contact sensing platform.

Outline• History– Where Live Social Semantics came from

• Sociopatterns.org• Tagora Project

• LSS Architecture– Tracking Face-to-Face Contacts– Integrating and Managing Data– Building Profiles of Interest

• LSS at ESWC2009 and HT2009• Future Work

Sociopatterns.org

http://www.sciencegallery.com/infectious

This projects aims to shed light on patterns in social dynamics and coordinated human activity. We do so by developing and deploying an experimental social interaction sensing platform. This platform consists of portable sensing device and software tools for aggregating, analyzing and visualizing the resulting data.

tagora-project.eu

• Automatic Generation of Profiles of Interest using Cross-Folksonomy Data

[2] Szomszor, M., Alani, H., Cantador, I., O'Hara, K. and Shadbolt, N. (2008) Semantic Modelling of User Interests based on Cross-Folksonomy Analysis. In: 7th International Semantic Web Conference (ISWC), October 26th - 30th, Karlsruhe, Germany.

Can you tell what my interests are?

5

LSS – Proposed Features• Contact Histories– “Hey, I remember talking to this person, but I don’t

know their name / email / institution”• People you might know – “Who are the people in my social networks /

community of practice who are also attending the conference? What papers are they presenting”

• Profiles of Interest– “I’d like to expose the things that I’m interested in

to other participants, including extra-academic data based on my folksonomy interactions”

Features NOT Required• We are not concerned with tracking an

individual’s exact location. The focus of LSS is to log social interactions (face-to-face contact)

• We don’t want to track people outside the conference area

Participation• Participation is voluntary• Association of your RFID badge to your real

identity is voluntary– You can participate using only an anonymous id

LSS Stack

Live Social Semantics

Web2.0 Linked DataDelicious

Real World

semanticweb.org

acm, dblp, citeseer …

rkbexplorer.com

Social Semantics

ArchitectureW

eb B

ased

Sys

tem

sRe

al W

orld

4store

ExtractorDaemon

Delicious

Flickr

Lastfm

Facebook Connect API

RKBExplorer.com

data.semanticweb.org

ProfileBuilder

dbtune.org

dbpedia.org

TAGora SenseRepository

COP + Publications

Publications

Social TaggingSocial Networks

Contacts

mbid - > dbpedia uritag -> dbpedia uri

Loca

l Ser

ver

Aggr

egat

or

RDF

Cach

eRFID Readers

RFID Badges

Real World Contact Data

ConsumesTagging Data

Returns Profileof Interests

Active RFID Contact Tracking

Local Server

ESWC2009 Map

Active RFID Proximity Detection

• spatial resolution ~ 1 meter• anisotropy - face-to-face• temporal resolution ~ 5-20 seconds• unobtrusive• Scalable

RDF Representation of Contact Datahttp://tagora.ecs.soton.ac.uk/

LiveSocialSemantics/eswc2009/1410

http://tagora.ecs.soton.ac.uk/LiveSocialSemantics/eswc2009/contact/day3/1410/1515

http://tagora.ecs.soton.ac.uk/LiveSocialSemantics/eswc2009/1515

hasPhysicalContact

"2009-06-03"^^<http://www.w3.org/2001/XMLSchema#date>

"00:01:43"^^<http://www.w3.org/2001/XMLSchema#time>

contactWith

contactDate

contactDuration

How are you connected?

Delicious

Folksonomies, The Semantic Web, and Movie Recommendation

Live Social Semantics

www.tagora-project.eu

Publications

Projects

CiroCattuto

MartinSzomszor

Distinct, Separated Identity Management

http://tagora.ecs.soton.ac.uk/delicious/martinszomszor

http://tagora.ecs.soton.ac.uk/flickr/7214044@N08@N08

http://tagora.ecs.soton.ac.uk/lastfm/count-bassy

http://tagora.ecs.soton.ac.uk/facebook/613077109

MartinSzomszor

http://data.semanticweb.org/person/martin-szomszor/

http://southampton.rkbexplorer.com/id/person-05877

http://tagora.ecs.soton.ac.uk/LiveSocialSemantics/eswc2009/1410

http://tagora.ecs.soton.ac.uk/LiveSocialSemantics/eswc2009/foaf/1

Delicious Tagging and Network

Flickr Tagging and Contacts

Lastfm favourite artists and friends

Facebook contacts

RFID Contact Data

Conference Publication Data

Past Publications, Projects, Communities of Practice

Delicious Last.fm Flickr Facebook

Identity Integration Tag Integration

Semantic User Profiles

…

FOAF DBpedia + Wordnet

Making Sense of Folksonomies

RDF Representation of Tagging Data

hasDomainTag

segmentTag (f)

Tag

Tagger Post

DomainTag

GlobalTag

UserTag

Resource

xsd:integer

xsd:integer

xsd:integerhasUserFrequency

hasGlobalFrequency

hasDomainFrequency hasGlobalTag

usesTag

isFilteredTo

rdfs:label

xsd:string

hasPost

TagSegment

FinalTagSegment

hasTagSequence (f)

hasNextSegment (f)

taggedResourcetaggedOn

xsd:dateTime

tagAssigned

http://tagora.ecs.soton.ac.uk/schemas/tagging#

http://www.w3.org/2001/XMLSchema#

(f) = functional property

property subclass

didYouMean

Tag Disambiguation• Term vector similarity– Term vector from tag co-occurrence – Term vector for each suggested Dbpedia disambiguation

page

18

appl

e, in

c, co

mpu

ter,

..

apple, tree, fruit, ..apple, iphone, co

mputer, ..

appl

e, fi

lm, 1

980,

..

Profile Building• 1) Disambiguate Tags– cosine similarity between user co-occurrence vector

and term frequency vector from concept– Choose Sense if above threshold (0.3) or single sense

• 2) Calculate Interest Weights– weight w = fr ur , where fr is the total frequency of ∗

all tags disambiguated to sense r, and ur is a a time decay factor. The factor ur = days(r)/90⌈ ⌉

• 3) Create Interest List– If more than 50 interests are suggested, we rank by

weight and suggest the top 50– Users must verify the list before it is published

Profiles of Interest

Profiles of Interest

http://tagora.ecs.soton.ac.uk/LiveSocialSemantics/eswc2009/foaf/1

foaf:Person

http://tagora.ecs.soton.ac.uk/delicious/martinszomszor

foaf:Persontagging:Tagger

http://tagora.ecs.soton.ac.uk/delicious/tag/ontologymapping

tagging:UserTag

http://tagora.ecs.soton.ac.uk/tag/ontologymapping

tagging:GlobalTag

http://dbpedia.org/resource/Semantic_Integration

TAGora Sense Repository

tagging:UsesTag

owl:SameAs

tagging:hasGlobalTag

disam:hasPossibleSense

foaf:interest

Participation• European Semantic Web Conference (ESWC2009)

– Attendees 305– 187 Participated in LSS– 139 of them registered online

• Hypertext (2009)– Attendees 150– 113 Participated in LSS– 97 of them registered online

• Totals– 455 Attendees– 300 Participated in LSS– 236 registered online– 21% people took a badge but did not register

Declaration of SNS Accounts

Facebook Delicious lastFM Flickr TOTAL

ESWC 78 59 57 52 246

HT 48 28 26 23 125

TOTAL 126 87 83 75 371

Number of SNS Accounts Given

0 1 2 3 4 TOTALESWC 49 36 28 13 13 139HT 35 18 23 8 13 97TOTAL 84 54 51 21 26 236

Profiles of Interest

Global Delicious Flickr LastFMConcepts Generated

2114 1615 456 43

Concepts Removed

449(21%)

307(19%)

133(29%)

9(21%)

Accuracy of DBPedia Senses

Survey Results

Option Reason No. Users %

a don’t have those accounts (or rarely use them) 16 44%

b use different networking sites 10 28%

c don’t like to share them 3 8%

d didn’t get a chance to share them (e.g. no computer, slow internet)

6 17%

e other 1 3%

TOTAL 36 100%

After the conference, we emailed the users who did register on our site, but did not enter any social networking accounts. The aim was to understand the reasons why:

Future Work• Allow individuals to link to their own foaf

profiles– Some semantic web searching already done

• More SNS sites:– Twitter, LinkedIn, etc…

• Document and Advertise Linked Data Interface– Support other applications in exploiting the data

• Recommend Contacts– What features are most predictive of face-to-face

contact

Building Better Profiles

• What tags correspond to interests?– Locations and topics are useful, but other terms

are not• TF / IDF Approach– It’s not that useful to find out we are all interested

in RDF and the Semantic Web• Making use of the Category hierarchy– If I’m interested in Facebook, Flickr, Last.fm,

Delicious, etc, I can extrapolate the interest Online_Social_Networks

Thanks for your attention

Presence of Attendees HT2009

Number of cliques HT2009