Bowling Alone and Trust Decline in Social Network Sites Paolo Massa, Martino Salvetti, Danilo Tomasoni FBK - Trento, Italy [email protected] http://www.gnuband.org License: Creative Commons (see last slide for details)
Bowling Alone and Trust Decline in Social Network Sites
Jan 20, 2015
In this paper we analyze the community of a social network site, Advogato. The peculiar characteristics of Advogato is that users can explicitly express weighted trust relationships among themselves. We conduct a longitudinal analysis of the trust network over a time period of 4 years, exploring the community as it grew from a knit circle of 300 users to an society of almost 6500 individuals. We report the changes over time of standard indexes in social network analysis such as clustering and degrees of separation. We then focus on specific measures about trust such as reciprocity and changes over time of average trust. A decline in trust is observed as the community grows. Following what we believe to be the first empirical analysis of trust evolution over time in a real community, we conclude suggesting how the availability of data about human relationships in social network sites is opening up the possibility of monitoring changes in trust in real time. In order to foster this research line, we released the datasets and the code we used in our analysis.
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Bowling Alone and Trust Decline in
Social Network Sites
Paolo Massa, Martino Salvetti, Danilo TomasoniFBK - Trento, Italy
[email protected]://www.gnuband.org
License: Creative Commons (see last slide for details)
Outline
1. Social Network Sites and Trust Networks
2. Longitudinal SNA on Advogato.org (over 4 years) and related work
3. Experiments and Results
Social Network Site (SNS)
“Web-based services that allow individuals to
(1) construct a public or semi-public profile within a bounded system,
(2) articulate a list of other users with whom they share a connection, and
(3) to view and traverse their list of connections and those made by others within the system.
The nature and nomenclature of these connections may vary from site to site.” [boyd]
Social Network Sites
Social networks: Facebook, Flickr, Youtube, del.icio.us
BUT ALSO
E-marketplaces: Ebay.com, Epinions.com, Amazon.com
News sites: Slashdot.org, Kuro5hin.org, Digg.com
Job sites: LinkedIn, Ryze, ...
Open Source Developer communities: Advogato, Github
Hosting networks: Couchsurfing, Hospitalityclub
Great opportunity for research!
Trust statements expressed by raph
Advogato trust network
Advogato = SNS for Open Source developers
http://www.advogato.org
Possible to express trust in other users on 4 levels: Master (mapped as T(A,B)=1.0 in [0,1]) Journeyer (mapped as T(A,B)=0.8 in [0,1]) Apprentice (mapped as T(A,B)=0.6 in [0,1]) Observer (mapped as T(A,B)=0.4 in [0,1])
WEIGHTED RELATIONSHIPS!!!
What is trust?
Definition
[PICTURE]
What is trust?
Definition
[PICTURE]
Trust statement is an explicit judgement given by a user about another user:
Example: ”I (Alice) trusts Bob as 0.6 in [0,1]”
Very general definition: it fits many situations (Flickr, Facebook, Linkedin, Ebay, ...)
Alice Bob0.6
What is trust?
Definition
[PICTURE]
Aggregate all the trust statements to produce a trust network
Node ~ userDirect edge ~ trust statement
Properties of Trust:- weighted (0=distrust, 1=max trust)- subjective- asymmetric- context dependent
Alice
Carol
0.9
Bob1
0Dave
0.6
0.2
What is trust?
Definition
[PICTURE]
CLAIM
Possible to adopt the trust network metaphor for every social network site (facebook, flickr, delicious, ... the web
too)
Why Advogato? Today is the only one with Weighed directed trust relationships available
Outline
1. Social Network Sites and Trust Networks
2. Longitudinal SNA on Advogato.org (over 4 years) and related work
3. Experiments and Results
Advogato social network datasets
Collected many snapshots of the social network (60+)
First dataset: 2000-02-25 (early days, 300 users)
Last dataset: 2004-10-28 (mature community)
(all datasets released on www.Trustlet.org)
We studied evolution of trust in time in a community
Related work1) Social networks topology (and evolution): here we study trust
relationships
2) WorldValuesSurvey 1000+ interviewees for 97 countries (1981 to 2007)
One question: “Would you say that most people can be trusted?” mid-1990s: “yes” ranges from 65% (Norway) to 3% (Brazil)
Trust correlates positively with economy growth and welfare. Negatively with inequality and corruption. Studies on evolution of trust over time.
3) Putnam “Bowling alone: America's Declining Social Capital” [putnam]: ~500,000 interviews in US (1975-2000) → decline of social capital over time (belong to fewer orgs (-58%), know their neighbors less (-35%), ...)
Motivation for this work: Is it possible to study evolution of trust as the last 2 examples BUT at the finer-grained level of the single human?
Yes! Thanks to Social Network Sites! Here we analyze a real social network (“I trust Mary as 0.6”) and not answer to interviews! Just a beginning!
Outline
1. Social Network Sites and Trust Networks
2. Longitudinal SNA on Advogato.org (over 4 years) and related work
3. Experiments and Results
Experiments on Advogato networks
- basic statistics such as number of nodes and edges
- traditional social network analysis indexes such as clustering and mean degree of separation
- measures related to weighted trust such as frequency of trust statements, discordance in reciprocated trust statements and changes in average trust
(all of them over 4 years time!)
What I'm going to show you?A measure (y axis)over time (x axis)
So its evolution in time
Up to2004-10-28
Since 2000-02-25
All datasets andPython code released onwww.trustlet.org(Test your hypos!)
Number of users on Advogato
300 users(in 2000-02-25)
6482 users(in 2004-10-28)
Evolutionfrom a close-knit circle(first users knew the funders and
each other)
to a mature society (new users joined it via web)
Number of trust edges on Advogato
2109 trust edges(in 2000-02-25)
47943 trust edges(in 2004-10-28)
As expected,#edges, just as #users, grows
Mean outdegree (outgoing trust statements per user)
Surprised?It's a REAL social network!
Important to study REALsocial network and not
synthetized onesbecause of un-
expected
activitypatterns
(1) 2000-02-25: 14.0 (300 users)
(2) 2000-07-18: 16.7 (1454 users)what did the 1154 new users did in 5 months?No datasets ;(
(3) 2000-08-11: 15.1 (1880 users)
% users in the main strongly connected component (set in which everyone is reachable by everyone)
Declinefrom 62%
down to 48%In the ol' days, everyone
knew each other,then, new unknown users
start to join (smaller subcommunities)
...
Clustering coefficientSame pattern:
decline!The network
becomes more spread over time
Mean degrees of separation(stabilizes over 3.5)
Not SIX???6 degrees of separation
is more a buzzword than reality
Percentage of trust statements that get reciprocated
In Advogato, it stabilizes ~36%
In Flickr, ~66%Facebook, 100% by design
(depends on the socio-technological system)
Notreciprocated
ReciprocatedMaster
ReciprocatedJourneyer
ReciprocatedApprentice
ReciprocatedObserver
Master 75.51% 10.22% 10.19% 3.10 % 0.97 %
Journeyer 55.26% 7.54% 27.06% 7.90% 1.70 %
Apprentice 57.76% 5.36% 18.44% 15.59% 2.85 %
Observer 80.16% 3.00% 7.12% 5.10% 4.62 %
Reciprocation matrix: what (row) reciprocated how (column)
What is trust?
Definition
[PICTURE]
% trust values on edges
Average trust in the community as expressed by Advogato users over time
Trust is decliningas society grows.
A normal pattern common to every
society?
Conclusions
First longitudinal analysis of trust evolution in a social community (4 years, from 300 users to ~6500)
Experimental evidence of trust decline
Goal: create real-time global trust monitor (social relationships in time from all social network sites!)
For now, datasets and python code released at www.trustlet.org
Bibliography
[boyd] boyd, d. and Ellison, N. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1):210-230.
[newman] Newman, M. E. J. (2001). Clustering and preferential attachment in growing networks. Phys. Rev. E 64
[mislove] Mislove, A., Koppula, H. S., Gummadi, K. P., Druschel, P., and Bhattacharjee, B. (2008). Growth of the flickr social network. In WOSP '08: Proceedings of the first workshop on Online social networks, pages 25-30, New York, NY, USA. ACM.
[putnam] Putnam, R. D. (1995). Bowling Alone: America's Declining Social Capital. Journal of Democracy, Volume 6, Number 1
[barabasi] Barabasi, A.-L. (2003). Linked: How Everything is Connected to Everything Else and What it Means for Business and Everyday Life. Plume Books.
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