EXISTING RESEARCHANDFUTURE RESEARCHAGENDADR MATTHEW ROWERESEARCH ASSOCIATEKNOWLEDGE MEDIA INSTITUTEhttp://www.matthew-rowe...
The Big Picture 1        2006-2010: Ph.D.: ‘Disambiguating Identity Web References using Social                 Data’. Th...
Digital Identity       Digital Identity                                                                                   ...
Digital Identity       Digital Identity                                                                                   ...
Digital Identity       User Behaviour                                                                                     ...
Digital Identity       User Behaviour                                                                                     ...
Digital Identity       User Behaviour                                                                                     ...
The Big Picture - Revisit 7     Ph.D.                 Research Associate        Future Work     2006-2010             2010...
Digital Identity       Identity Lifecycles                                                                                ...
Digital Identity       Identity Diffusion                                                                                 ...
The Big Picture - Recap 10      Ph.D.                Research Associate        Future Work      2006-2010            2010-...
11         Questions?               http://www.matthew-rowe.com               m.c.rowe@open.ac.ukDr Matthew Rowe - Existin...
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Existing Research and Future Research Agenda

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Existing Research and Future Research Agenda

  1. 1. EXISTING RESEARCHANDFUTURE RESEARCHAGENDADR MATTHEW ROWERESEARCH ASSOCIATEKNOWLEDGE MEDIA INSTITUTEhttp://www.matthew-rowe.comm.c.rowe@open.ac.uk
  2. 2. The Big Picture 1 2006-2010: Ph.D.: ‘Disambiguating Identity Web References using Social   Data’. The University of Sheffield 2010-2012: Research Associate at the Knowledge Media Institute, The Open   University Ph.D. Research Associate Future Work 2006-2010 2010-2012 Digital Identity Digital Identity Identity Diffusion Lifecycles User Behaviour TimeDr Matthew Rowe - Existing Research and Future Research Agenda
  3. 3. Digital Identity Digital Identity Digital Identity Identity Diffusion Lifecycles User Behaviour 2   Personal information is spread across the Web: (a) identity theft, (b) lateral surveillance  Identity theft costs the UK government £1.2 billion per annum (Get Safe Online, 2010)   Manually tracking web citations is time-consuming and repetitive  57% of web users perform ‘vanity’ searches (Pew Internet Report, 2010) How can identity web references be disambiguated automatically? Seed data leveraged from Social Web Systems   Information extracted from candidate citations and semantic model built   Devised three disambiguation methods that combine data mining with semantics  Dr Matthew Rowe - Existing Research and Future Research Agenda
  4. 4. Digital Identity Digital Identity Digital Identity Identity Diffusion Lifecycles User Behaviour 3   Seed Data generation:  Large overlap between offline social networks and online social networks  Exporting semantic social graphs from disparate social web systems (Twitter, Facebook)  Machine-readable user profile and social network information  Interlinking social graphs from disparate social web systems   Disambiguation methods  Rule-based:infer relations between social data and web resources  Graph-based: random walks over a graph space and clustering  Semi-supervised machine learning: classify web citations and learn from classifications   Findings:  Socialdata provides necessary seed data to disambiguate web citations  Achieve best performance using semi-supervised methods, outperforming several baselines (unsupervised methods) Rowe and Ciravegna. Disambiguating Identity Web References using Web 2.0 Data and   Semantics. Journal of Web Semantics. 2010  http://www.matthew-rowe.com/?q=thesisDr Matthew Rowe - Existing Research and Future Research Agenda
  5. 5. Digital Identity User Behaviour Digital Identity Identity Diffusion Lifecycles User Behaviour 4   Attention Patterns on Social Web Systems   How is user behaviour associated with heightened attention?   Developed a machine learning approach to:   Identify seed posts   Predict discussion lengths   User Modelling: social network properties, topical focus, community affinity   Patterns associated with increased attention:  Twittter: greater broadcast spectrum  Boards.ie: greater community affinity, focussed users  SAP: less community messages, popular users (frequently provide answers) Rowe et al. Anticipating Discussion Activity on Community Forums. 3rd IEEE International Conference on Social   Computing, Boston, USA. 2011 Rowe et al. Predicting Discussions on the Social Semantic Web. Extended Semantic Web Conference, Heraklion,   Crete. 2011 Wagner et al. What catches your attention? An empirical study of attention patterns in community forums.   International Conference on Weblogs and Social Media, Dublin, Ireland. 2012Dr Matthew Rowe - Existing Research and Future Research Agenda
  6. 6. Digital Identity User Behaviour Digital Identity Identity Diffusion Lifecycles User Behaviour 5 Behaviour Analysis in Online Communities    How can the contextual notion of behaviour be captured?  What is the relation between community behaviour and health?  Modelled user behaviour along six dimensions:  Focus Dispersion, Initiation, Contribution, Popularity, Engagement, Content Quality  Modelled behaviour using semantic web technologies:  Behaviour Ontology – capturing contextual notion of behaviour  Inference rules – identifying the role of a given user  Mined roles, and associated behaviour, on a given platform  Correlated the time-series role composition of communities and with health indicators  Found certain roles to be associated with decreases in community health  E.g. Expert Initiators linked to community churn  Roweet al. Community Analysis through Semantic Rules and Role Composition Derivation. Journal of Web Semantics (in press). 2012Dr Matthew Rowe - Existing Research and Future Research Agenda
  7. 7. Digital Identity User Behaviour Digital Identity Identity Diffusion Lifecycles User Behaviour 6   Churn  Churn is the loss of users from a service (telecommunications/social network, online community)  Goal: predict churners and identify churn patterns  Using social network features (i.e. centrality) provided accurate information for churn detection  Found:  Differing churn patterns between communities  Central users churn in some communities, while peripheral users churn in others  Currently exploring: Churn diffusion and topological effects  Karnstedtet al. The Effect of User Features on Churn in Social Networks. ACM Web Science Conference 2011, Koblenz, Germany. 2011Dr Matthew Rowe - Existing Research and Future Research Agenda
  8. 8. The Big Picture - Revisit 7 Ph.D. Research Associate Future Work 2006-2010 2010-2012 Digital Identity Digital Identity Identity Diffusion Lifecycles User Behaviour TimeDr Matthew Rowe - Existing Research and Future Research Agenda
  9. 9. Digital Identity Identity Lifecycles Digital Identity Identity Diffusion Lifecycles User Behaviour 8  Identity is developed and shaped over time through developmental stages (Eriksson, 1959)  Ego-identity is the ideal that people pursue, while identity is a person’s present state (Bosma et al., 1994)  How are digital identities shaped online? Do the stages resonate with Eirksson’s theories?  What development stages do they go through? Is there a common life cycle across systems?  In role analysis there are common transitions from one role to another What are the motivations behind digital identity formation and amendments?    Self-efficacy  Self-affirmation Understanding identity lifecycles leads to:    Better recommendations (followees, products, content)  Tracking of disseminated personal information  Identifying users susceptible to ‘stealing reality’ attacks (Altshuler et al., 2011)Dr Matthew Rowe - Existing Research and Future Research Agenda
  10. 10. Digital Identity Identity Diffusion Digital Identity Identity Diffusion Lifecycles User Behaviour 9 Identity Diffusion is the propagation of identity attributes through social systems    I.e. the adoption of defining characteristics from neighbours What network effects are associated with identity diffusion?    Smallcore of central users found to be influential in protest recruitment (Gonzalez-Bailon et al., 2011)  Core web sites found to influence the spread of memes (Gomez-Rodriguez et al., 2012) What is the role of passive/active networks on identity formation?    Behaviour adoption is maintained through social reinforcement (Centola, 2010) Local-level influence (i.e. homophily, inequity, balancing)    Weak-tied individuals in ego-networks influence adoption (Garg et al., 2011)  Inverse correlation between node influence and degree (Katona et al., 2011) What effects do community actions have on web presence and subscriber churn?    Onlinecommunity churn (Karnstedt et al., 2010), (Zhang et al., 2010), (Kawale et al., 2010)  Recently studied in the context of ego-networks (Quercia et al., 2012), (Kwak et al., 2011) Understanding and modelling identity diffusion leads to:    Identification of links between behaviour and churn from online systems  Enable understanding of reductions in web presence (Online marketing, brand promotion)Dr Matthew Rowe - Existing Research and Future Research Agenda
  11. 11. The Big Picture - Recap 10 Ph.D. Research Associate Future Work 2006-2010 2010-2012 Digital Identity Digital Identity Identity Diffusion Lifecycles User Behaviour TimeDr Matthew Rowe - Existing Research and Future Research Agenda
  12. 12. 11 Questions? http://www.matthew-rowe.com m.c.rowe@open.ac.ukDr Matthew Rowe - Existing Research and Future Research Agenda

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