Bowling Alone and  Trust Decline in  Social Network Sites
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Bowling Alone and Trust Decline in Social Network Sites

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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. ...

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 Bowling Alone and Trust Decline in Social Network Sites Presentation Transcript

  • Bowling Alone and Trust Decline in Social Network Sites
      • Paolo Massa , Martino Salvetti, Danilo Tomasoni
    • FBK - Trento, Italy
      • [email_address]
      • http://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 Bob 0.6
  • What is trust?
    • Definition
    • [PICTURE]
      • Aggregate all the trust statements to produce a trust network
      • Node ~ user
      • Direct edge ~ trust statement
    • Properties of Trust:
    • - weighted (0=distrust, 1=max trust)‏
    • - subjective
    • - asymmetric
    • - context dependent
    0.9 1 0.2 Alice Carol Bob 0 Dave 0.6
  • 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 work
    • 1) 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 to 2004 -10-28 Since 2000 -02-25 All datasets and Python code released on www.trustlet.org (Test your hypos!)‏
  • Number of users on Advogato 300 users (in 2000-02-25)‏ 6482 users (in 2004-10-28)‏ Evolution from 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 REAL social network and not synthetized ones because of un- expected activity patterns (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)‏ Decline from 62% down to 48% In the ol' days, everyone knew each other, then, new unknown users start to join (smaller subcommunities)‏ ...
  • Clustering coefficient Same 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)‏
  • 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 declining as 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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