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The Opinion Evaluation Network. Nikos Korfiatis Computer Technology Institute (CTI) University of Patras, Greece & Royal Institute of Technology (KTH), Stockholm. My FOAF profile.
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The Opinion Evaluation Network Nikos Korfiatis Computer Technology Institute (CTI) University of Patras, Greece & Royal Institute of Technology (KTH), Stockholm
My FOAF profile • <foaf:knows> Ambjorn Naeve (Royal Institute of Technology, Stockholm) and Miltiades Lytras (University of Patras,Greece) • <foaf:project> Doing my master thesis on Interactive Systems Engineering (KTH, Stockholm) • <foaf:….> Soon to start my PhD on Computational Sociology and Semantic Web Presentation in the PhD Summer School / Prolearn
Computational Sociology • JABW ( Just another Buzzword…) synonymous with Social Network Analysis but includes analytical simulation and experimental techniques over network data • The development and evaluation of formal models on information acquired from social activities expressed via the use of information enhanced means • Grounded on 1930’s by Jacob Moreno initially as a part of Experimental and Social Psychology Presentation in the PhD Summer School / Prolearn
Aspects of Computational Sociology • Network Models • Clique Formation • Prestige and Centrality • Structural Equivalence • Social Simulation • Micro and Macro Analytical Models for Simulation of Agents Presentation in the PhD Summer School / Prolearn
Background Hypothesis • Social actors are independent proactive entities and the amount of social relationship among them has important consequences for every individual • Famous Social Network Cases • The Six Degrees of Separation (also a famous movie). Derives from Miligram’s Experiment in 1970’s • The Case of Social Capacity (The magic number 150…) • Epidemics Research (with application to computer viruses) Presentation in the PhD Summer School / Prolearn
Information Overload and Filtering • Too much Information • Learning Resources • Different Skills • Context must be takeninto account • Effectiveness of user modeling and recommender systems Presentation in the PhD Summer School / Prolearn
Slashdot.org • An already deployed opinion evaluation system • My “Karma” reflects my prestige Presentation in the PhD Summer School / Prolearn
Opinion Evaluation • Social Recommendation of what resource is useful for your current context of use and current needs • But…. Also who is able to provide you a concrete answer on your problems (for instance a continuous competency analysis map) • Provide a way to link people, interests, with values and artifacts (Books, Decisions but also Learning Objects) Presentation in the PhD Summer School / Prolearn
Methodology • Computational Sociology (CS) • Social Network Analysis • Centrality and Prestige • Cliques and Cohesive Subgroups • Flows and Cycles on Social Graphs • Social Simulation • Predict how social structures are evolved • Evaluate Use Cases and Activities • Semantic Web • An Input for CS models ( Data ) • FOAF Interactions • Provide meaning of Social Interactions Presentation in the PhD Summer School / Prolearn
Interdisciplinary Research • Customer Behavior (Marketing) • Rater Agreement Statistics • A class of statistical metrics that permits the use of alternative scales on evaluating the same research question • Collaborative Filtering • Algorithms for finding common interests Presentation in the PhD Summer School / Prolearn
An Ontology of Social Values • Let the raters agree on their rating scales (Rater Agreement Statistics) • Bipolar Scales (-1,1) • Likert Scales (-2,-1,0,1,2) • Etc,.. • Let the raters publish their social values which are reflected using a rating scale (I like a book, I don’t like it) • Deploy and built the mechanisms and the formal models to combine these values using a unified ontology • Provide recommendations and deductions based on these models Presentation in the PhD Summer School / Prolearn
What can our research contribute to Prolearn • A tool for evaluation and customization of learning objects based on social context • Context Information is difficult to be acquired • User Modeling systems usually do not capture context ( eg. Activities Running Simultaneously and in asynchronous mode) • We rely on relationships instead of metadata • Prestige and Centrality of who-is-who (Selfish, Collaborative) • A tool for acquisition and emergent evaluation of Competencies • Integration with existing tools (Edutella, teleconferencing) Presentation in the PhD Summer School / Prolearn