Slides of invited talk presented at ESF-COST conference on Future Internet and Society: A complex Systems Perspective

1. Semantics, Sensors, and the
Social Web
Harith Alani
Knowledge Media institute,
The Open University, UK
Future Internet and Society: A Complex Systems Perspective
Aquafredda di Maratea, Italy, 2-7 October 2010

2. Offline + online social networking
Who should
Anyone I I talk to? Where have I
know here? met this guy?
Where
should I go?
ESWC2010 2

3. Social Web Communities
Sept. 2008 3

4. Semantic Web + Social Web + RFIDs
<?xml version="1.0"?>!
<rdf:RDF!
xmlns="http://
tagora.ecs.soton.ac.uk/schemas/
tagging#"!
xmlns:rdf="http://www.w3.org/
1999/02/22-rdf-syntax-ns#"!
xmlns:xsd="http://www.w3.org/2001/
XMLSchema#"!
xmlns:rdfs="http://www.w3.org/
2000/01/rdf-schema#"!
xmlns:owl="http://www.w3.org/
2002/07/owl#"!
xml:base="http://
tagora.ecs.soton.ac.uk/schemas/
tagging">!
<owl:Ontology rdf:about=""/>!
<owl:Class rdf:ID="Post"/>!
<owl:Class rdf:ID="TagInfo"/>!
<owl:Class
rdf:ID="GlobalCooccurrenceInfo"/>!
<owl:Class
rdf:ID="DomainCooccurrenceInfo"/>!
<owl:Class rdf:ID="UserTag"/>!
<owl:Class
rdf:ID="UserCooccurrenceInfo"/>!
<owl:Class rdf:ID="Resource"/>!
<owl:Class rdf:ID="GlobalTag"/>!
<owl:Class rdf:ID="Tagger"/>!
<owl:Class rdf:ID="DomainTag"/>!
<owl:ObjectProperty
rdf:ID="hasPostTag">!
<rdfs:domain
rdf:resource="#TagInfo"/>!
</owl:ObjectProperty>!
<owl:ObjectProperty
rdf:ID="hasDomainTag">!
<rdfs:domain
rdf:resource="#UserTag"/>!
</owl:ObjectProperty>!
<owl:ObjectProperty
rdf:ID="isFilteredTo">!
<rdfs:range
rdf:resource="#GlobalTag"/>!
<rdfs:domain
rdf:resource="#GlobalTag"/>!
</owl:ObjectProperty>!
<owl:ObjectProperty
rdf:ID="hasResource">!
<rdfs:domain rdf:resource="#Post"/>!
<rdfs:range =…!

5. Live Social Semantics (LSS)
• Integration of physical presence and online information
• Semantic user profile generation
• Interest identification from distributed tagging activities
• Logging of face-to-face contact
• Social network browsing
• On-site and post-event support for social networking
• Analysis of online vs offline social behaviour
+ +
real-­‐world
social
contacts semantic
web
linked
data online
social
networks
5

6. Components of LSS
Communities of Practice Communities of Practice
rkbexplorer.com dbtune.org rkbexplorer.com
Publications Profile Builder dbpedia.org Publications Profile Builder
semanticweb.org semanticweb.org
ontology
Web-based Systems
("
!"
interests
data.semanticweb.org TAGora Sense Profile T
Delicious builderDelicious
rkbexplorer.com Repository
Extractor Extractor
Flickr publications, co-authorship networks Flickr m
Daemon Social Tagging mbid -> dbpedia uri Daemon Social Tagging
Social Networks tag -> dbpedia uri Social Networks
LastFM #" LastFM
'"
Facebook Connect API JXT Triple Store Facebook Connect API JXT Triple Store
Contacts social semantics Contacts
%"
URIs
Tag disambiguation
Social triple store Social
service Semantics
RDF cache
Aggregator
Semantics
RDF cache
Aggregator
contacts data
RFID
ID
Local Local
aders Readers
tags, networks
Real World
Server Server Real-World
Tag to URI Real-World
service
Contact Data Contact Data
&"
tags
ID $"
RFID
dges Badges
Visualization Web Interface Linked Data Visualization Web Interface
Linked data Web interface Visualization
6

7. But what is the Semantic Web anyway?

8. Semantic Web Layer Cake
8

9. RDF
!<rdfs:label>Harith RDF Description</rdfs:label>
!
!<foaf:firstname>Harith</foaf:firstname>!
!<foaf:surname>Alani</foaf:surname>!
!<foaf:phone rdf:resource="tel:+44-(0)
1908-659399"/>!
!<foaf:homepage rdf:resource="http://
people.kmi.open.ac.uk/harith/"/>!
!<foaf:publications rdf:resource="http://
kmi.open.ac.uk/publications/harith-alani"/>!
!<foaf:thumbnail rdf:resource="http://
kmi.open.ac.uk/img/members/harith-alani.jpg"/>!
!…!

10. Semantic triples and formal inference
<kmi:harithalani rdf:type foaf:Person>
<kmi:harithalani kmi:works-with isi:cirocattuto>
<fb:alain_barrat fb:friend fb:ciro_cattuto>
<kmi:works-with rdfs:subPropertyOf foaf:knows>
<fb:friend rdfs:subPropertyOf foaf:knows>
<kmi:harithalani foaf:knows isi:cirocattuto>
<fb:alain_barrat foaf:knows isi:cirocattuto>

11. Linked Open Data Cloud
2007
social networks
music
publications
geographic
general
millions of objects life science
Billions of triples
11

12. http://wiki.dbpedia.org/
12

13. 13

14. 14

15. The Rise of the Semantic Web
Facebook’s Open Graph
15

16. Semantic data sources
Communities of Practice Communities of Practice
rkbexplorer.com dbtune.org rkbexplorer.com
Publications Profile Builder dbpedia.org Publications Profile Builder
semanticweb.org semanticweb.org
ontology
Web-based Systems
("
!"
interests
data.semanticweb.org TAGora Sense Profile T
Delicious builderDelicious
rkbexplorer.com Repository
Extractor Extractor
Flickr publications, co-authorship networks Flickr m
Daemon Social Tagging mbid -> dbpedia uri Daemon Social Tagging
Social Networks tag -> dbpedia uri Social Networks
LastFM #" LastFM
'"
Facebook Connect API JXT Triple Store Facebook Connect API JXT Triple Store
Contacts social semantics Contacts
%"
URIs
Tag disambiguation
Social triple store Social
service Semantics
RDF cache
Aggregator
Semantics
RDF cache
Aggregator
contacts data
RFID
ID
Local Local
aders Readers
tags, networks
Real World
Server Server Real-World
Tag to URI Real-World
service
Contact Data Contact Data
&"
tags
ID $"
RFID
dges Badges
Visualization Web Interface Linked Data Visualization Web Interface
Linked data Web interface Visualization
16

17. SW sources
conference
chair proceedings
chair
author
CoP
17

18. Social networking systems
Communities of Practice Communities of Practice
rkbexplorer.com dbtune.org rkbexplorer.com
Publications Profile Builder dbpedia.org Publications Profile Builder
semanticweb.org semanticweb.org
ontology
Web-based Systems
("
!"
Profile interests
data.semanticweb.org TAGora Sense T
Delicious builderDelicious
rkbexplorer.com Repository
Extractor Extractor
Flickr publications, co-authorship networks Flickr m
Daemon Social Tagging mbid -> dbpedia uri Daemon Social Tagging
Social Networks tag -> dbpedia uri Social Networks
LastFM #" LastFM
'"
acebook Connect API JXT Triple Store Facebook Connect API JXT Triple Store
Contacts social semantics Contacts
%"
URIs
Tag disambiguation
Social triple store Social
service Semantics
RDF cache
Aggregator
Semantics
RDF cache
Aggregator
contacts data
RFID
D
Local Local
aders Readers
tags, networks
Real World
Server Server Real-World
Tag to URI Real-World
service
Contact Data Contact Data
&"
tags
D $"
RFID
dges Badges
Visualization Web Interface Linked Data Visualization Web Interface
Linked data Web interface Visualization
18

19. Social and information networks
19

20. http://sioc-project.org/
20

21. Making Sense of Folksonomies
Semantic User Profiles
FOAF DBpedia + Wordnet
Identity Integration Tag Integration
Delicious Last.fm … Flickr Facebook
• Tag ambiguity, misspellings, redundancy
• No semantic structure
• Distributed and disintegrated personal tag clouds
• Disconnected social network islands

22. Merging social networks
22

23. Tag structuring
23

24. Tag Filtering Service
Semantic modeling
Semantic analysis
Collective intelligence
Statistical analysis
Syntactical analysis

25. Tag Filtering Service

26. Tag Disambiguation
• Term vector similarity
• Term vector from tag co-occurrence
• Term vector for each suggested Dbpedia disambiguation
page
Co-occurring
80, ..
tags in the
whole
folksonomy
film, 19
User tags
regardless of
the resource
(Period of Time)
apple,
co-occurring
tags in the
same resource
, ..
ree , fruit
ap ple, t User Tags co -
occurring in the
same resource
26

27. From Tags to Semantics
27

28. Tags to User Interests
• Based on 72 POIs verified by users
Global Delicious Flickr lastFM
Concepts 2114 1615 456 43
generated
Concepts 449(21%) 307(19%) 133(29%) 9(21%)
removed
Only 15% of rejected interests
had incorrect Dbpedia matching
Phd candidates?
28

29. From raw tags and social relations
to Linked Data
Collective
intelligence
User raw Semantic
data data
Linked
data
ontologies

30. Communities of Practice Communities of Practice
rkbexplorer.com dbtune.org rkbexplorer.com
Publications Profile Builder dbpedia.org Publications Profile Builder
semanticweb.org semanticweb.org
ontology
Web-based Systems
("
!"
interests
data.semanticweb.org TAGora Sense Profile T
Delicious builderDelicious
rkbexplorer.com Repository
Extractor Extractor
Flickr publications, co-authorship networks Flickr m
Daemon Social Tagging mbid -> dbpedia uri Daemon Social Tagging
Social Networks tag -> dbpedia uri Social Networks
LastFM #" LastFM
'"
Facebook Connect API JXT Triple Store Facebook Connect API JXT Triple Store
Contacts social semantics Contacts
%"
URIs
Tag disambiguation
Social triple store Social
service Semantics
RDF cache
Aggregator
Semantics
RDF cache
Aggregator
contacts data
RFID
ID
Local Local
aders Readers
tags, networks
Real World
Server Server Real-World
Tag to URI Real-World
service
Contact Data Contact Data
&"
tags
ID $"
RFID
dges Badges
Visualization Web Interface Linked Data Visualization Web Interface
Linked data Web interface Visualization
30

31. SocioPatterns platform
31

32. Convergence with online social networks
leverage social context 32

33. Communities of Practice Communities of Practice
rkbexplorer.com dbtune.org rkbexplorer.com
Publications Profile Builder dbpedia.org Publications Profile Builder
semanticweb.org semanticweb.org
ontology
Web-based Systems
("
!"
interests
data.semanticweb.org TAGora Sense Profile T
Delicious builderDelicious
rkbexplorer.com Repository
Extractor Extractor
Flickr publications, co-authorship networks Flickr m
Daemon Social Tagging mbid -> dbpedia uri Daemon Social Tagging
Social Networks tag -> dbpedia uri Social Networks
LastFM #" LastFM
'"
Facebook Connect API JXT Triple Store Facebook Connect API JXT Triple Store
Contacts social semantics Contacts
%"
URIs
Tag disambiguation
Social triple store Social
service Semantics
RDF cache
Aggregator
Semantics
RDF cache
Aggregator
contacts data
RFID
ID
Local Local
aders Readers
tags, networks
Real World
Server Server Real-World
Tag to URI Real-World
service
Contact Data Contact Data
&"
tags
ID $"
RFID
dges Badges
Visualization Web Interface Linked Data Visualization Web Interface
Linked data Web interface Visualization
33

35. Live Social Semantics
Deployed at:
Participation
Event Attendees RFIDs LSS
collected accounts
ESWC09 300 187 139
HT09 150 113 97
ESWC10 310 175 132
Total 760 475 368

36. Declaration of SNS Accounts
Facebook Delicious lastFM Flickr TOTAL
ESWC09 78 59 57 52 246
HT09 48 28 26 23 125
Facebook Twitter TOTAL
ESWC 79 47 126
2010

37. Survey of users with no SNS accounts
• 84 registered with no SNS
accounts
• 36 responded to our survey
• Some used LinkedIn or xing
• This survey does not include
conf attendees who did not
participate in LSS
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 6 17%
computer, slow internet)
e other 1 3%
TOTAL 36 100% 37

38. Degree
• Degree: number of other 10
2
participants with whom an
attendee has interacted
1
10 1 2
10 10
ESWC2010
Total interaction time
• Total time: total time spent in 10
4
interaction by an attendee
3
10 3 4 5
10 10 10
• Link weight: total time spent in 4 Links’ weights
10
F2F interaction by a pair of 3
10
returning attendees in 2010, 2
10
versus the same quantity 1
10 1 2 3 4 5
measured in 2009 10 10 10 10 10
ESWC2009
38

39. Offline networking vs online networking
Users with Facebook and Twitter accounts in ESWC 2010
• people who have a large number of friends on Twitter and/or Facebook don’t seem to
be the most socially active in the offline world
39

40. Average seniority of neighbours in F2F networks
5
se
Avgnn
seniority of the neighbours
Average seniority of neighbors
se weighted averages
withnn,w
4
senn,max
Seniority of user with strongest link
3
2
1
0
0 5 10
seniority (number of papers)
• No clear pattern is observed if the unweighted average over all neighbours in the
aggregated network is considered
• A correlation is observed when each neighbour is weighted by the time spent with the
main person
• The correlation becomes much stronger when considering for each individual only the
neighbour with whom the most time was spent
40
• Similar results with h-index is considered as a measure of seniority

41. Scientific seniority vs Twitter followers
• Comparison between people’s scientific seniority and the number of people following
them on Twitter
• Most senior scientists are not the mostly followed on Twitter, and vice versa
41

42. Conference Chairs
all chairs all chairs
participants 2009 participants 2010
2009 2010
average degree 55 77.7 54 77.6
average strength 8590 19590 7807 22520
average weight average 159 500 141 674
number of events per 3.44 8 3.37 12
edge
• Conf chairs interact with more distinct people (larger average degree)
• Conf chairs spend more time in F2F interaction (almost three times as much as a
random participant)

43. Networking with online and offline ‘friends’
Characteristics all users coauthors Facebook Twitter
friends followers
average contact 42 75 63 72
duration (s)
average edge weight 141 4470 830 1010
(s)
average number of 3.37 60 13 14
events per edge
• Individuals sharing an online or professional social link meet much more often than
other individuals
• Average number of encounters, and total time spent in interaction, is highest for co-
authors

44. Limitations and future work
• Data is naturally sparse,
– not all conference attendees participated in LSS
– not all users participated in all LSS deployments
– many F2F contacts take place outside the RFID reader perimeters (e.g. at the bar,
restaurant, beach!)
• Social networks and their analysis is influenced by many parameters and
types of relationships
– Results might contain some bias due to data limitation to LSS users only, and to
data and attendees of our conferences
– Other parameters: age, affiliation, memberships, non-CS conferences, time (when
SNS account was created, when a ‘friendship’ link was added), SNS usage
• Richer user profiles
– currently building models and tools for generating rich user profiles to represent
user’s activities in various SNS
– Such profiles can then be analysed to identify usage and social behaviour,
influence, trends, and interests
44

45. Live Social Semantics core team
Wouter van Den Broeck Alain Barrat Martin Szomszor
ISI, Turin CPT Marseille & ISI CeRC, City University, UK
Ciro Cattuto Harith Alani
ISI, Turin KMi, UK
References:
• Barrat, A., et al. (2010) Social dynamics in conferences: analyses of data from the Live Social Semantics
application. In 9th International Semantic Web Conference (ISWC), China.
• Szomszor, M., et al. (2010) Semantics, Sensors, and the Social Web: The Live Social Semantics experiments.
Extended Semantic Web Conference (ESWC), Crete.
• Broeck, W., et al. (2010) The Live Social Semantics application: a platform for integrating face-to-face presence
with on-line social networking, Workshop on Communication, Collaboration and Social Networking in Pervasive
Computing Environments (PerCol), IEEE PerCom, Mannheim.
• Alani, H., et al. (2009) Live Social Semantics. In 8th International Semantic Web Conference (ISWC), US.
45