This document summarizes a PhD thesis presentation on developing a context management framework to filter social streams and recommend the most relevant updates. It proposes using contextual tag clouds generated from virtual and social sensors to represent users' contexts. An implementation was developed to test the approach. Evaluation results found that recommended social updates were 72% accurate and about half were deemed relevant to the posting context, depending on the type of social update. Future work is proposed to improve the quality of contextual tags and leverage additional sensors.
Tangible Contextual Tag Clouds towards Controlled and Relevant Social Inter...Adrien Joly
Presented by Adrien Joly at Bell Labs France during a "SKP" session, this slideshow includes a motivated introduction to his phd thesis subject about contextual filtering of social interactions, its technical approach relying on "contextual tag clouds", and its current state of research.
Tangible Contextual Tag Clouds towards Controlled and Relevant Social Inter...Adrien Joly
Presented by Adrien Joly at Bell Labs France during a "SKP" session, this slideshow includes a motivated introduction to his phd thesis subject about contextual filtering of social interactions, its technical approach relying on "contextual tag clouds", and its current state of research.
SP1: Exploratory Network Analysis with GephiJohn Breslin
ICWSM 2011 Tutorial
Sebastien Heymann and Julian Bilcke
Gephi is an interactive visualization and exploration software for all kinds of networks and relational data: online social networks, emails, communication and financial networks, but also semantic networks, inter-organizational networks and more. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Users interact with the visualization and manipulate structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypotheses, intuitively discover patterns or errors in large data collections.
In this tutorial we will provide a hands-on demonstration of the essential functionalities of Gephi, based on a real case scenario: the exploration of student networks from the "Facebook100" dataset (Social Structure of Facebook Networks, Amanda L. Traud et al, 2011). The participants will be guided step by step through the complete chain of representation, manipulation, layout, analysis and aesthetics refinements. Particular focus will be put on filters and metrics for the creation of their first visualizations. They will be incited to compare the hypotheses suggested by their own exploration to the results actually published in the academic paper afterwards. They finally will walk away with the practical knowledge enabling them to use Gephi for their own projects. The tutorial is intended for professionals, researchers and graduates who wish to learn how playing during a network exploration can speed up their studies.
Sébastien Heymann is a Ph.D. Candidate in Computer Science at Université Pierre et Marie Curie, France. His research at the ComplexNetworks team focuses on the dynamics of realworld networks. He leads the Gephi project since 2008, and is the administrator of the Gephi Consortium.
Julian Bilcke is a Software Engineer at ISC-PIF (Complex Systems Institute of Paris, France). He is a founder and a developer for the Gephi project since 2008.
Ethical and Legal Issues in Computational Social Science - Lecture 7 in Intro...Lauri Eloranta
Seventh lecture of the course CSS01: Introduction to Computational Social Science at the University of Helsinki, Spring 2015.(http://blogs.helsinki.fi/computationalsocialscience/).
Lecturer: Lauri Eloranta
Questions & Comments: https://twitter.com/laurieloranta
This short set of slides summarizes the characteristics of people who play specific roles in networks. In a social network analysis, people in these roles can be discovered by running mathematical algorithms through the social graphs. But you don't need to be an algorithm to spot some of these people in your networks!
A Perspective on Graph Theory and Network ScienceMarko Rodriguez
The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science.
This is an autobiographical lecture on my life (so far) with graphs/networks.
Introduction to Computational Social Science - Lecture 1Lauri Eloranta
First lecture of the course CSS01: Introduction to Computational Social Science at the University of Helsinki, Spring 2015. (http://blogs.helsinki.fi/computationalsocialscience/).
Lecturer: Lauri Eloranta
Questions & Comments: https://twitter.com/laurieloranta
Social Network Analysis & an Introduction to ToolsPatti Anklam
This presentation was delivered as part of an intense knowledge management curriculum. It covers the basics of network analysis and then goes into the different types of tool that support analyzing networks.
Is network theory the best hope for regulating systemic risk?Kimmo Soramaki
The presentation is organised around three policy questions:
1. How can we measure the systemic importance of a bank?
2. Can regulators promote a safer financial system by affecting its topology?
3. Is it possible to devise early-warning indicators from real-time data?
Social Network Analysis for Competitive IntelligenceAugust Jackson
How can CI teams apply the concepts of social network analysis to gain insight into the capabilities and plans of their competitors? Presented by Jim Richardson and August Jackson in April 2007 at the Society of Competitive Intelligence Professionals annual conference in New York City.
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...guest803e6d
A theoretically-grounded learning feedback tool suite, the Visible Effort (VE) Mediawiki extension, is proposed for optimizing online group learning activities by measuring the amount of equality and the emergence of social structure in groups that participate in Computer-Mediated Collaboration (CMC). Building on social entropy theory, drawn from Shannon’s Mathematical Theory of Communication, VE captures levels of CMC unevenness and group structure and visualizes them on wiki Web pages through background colors, charts, and tabular data. Visual information provides users entropic feedback on how balanced and equitable collaboration is within their online group are, while helping them to maintain it within optimal levels. Finally, we present the theoretical and practical implications of VE and the measures behind it, as well as illustrate VE’s capabilities by describing a quasi-experimental teaching activity (use scenario) in tandem with a detailed discussion of theoretical justification, methodological underpinning, and technological capabilities of the approach.
Applying research methods: Investigating the Many Faces of Digital Visitors &...Lynn Connaway
Connaway, L. S. (2018). Applying research methods: Investigating the Many Faces of Digital Visitors & Residents. Presented at the American University, March 29, 2018, Rome, Italy.
SP1: Exploratory Network Analysis with GephiJohn Breslin
ICWSM 2011 Tutorial
Sebastien Heymann and Julian Bilcke
Gephi is an interactive visualization and exploration software for all kinds of networks and relational data: online social networks, emails, communication and financial networks, but also semantic networks, inter-organizational networks and more. Designed to make data navigation and manipulation easy, it aims to fulfill the complete chain from data importing to aesthetics refinements and interaction. Users interact with the visualization and manipulate structures, shapes and colors to reveal hidden properties. The goal is to help data analysts to make hypotheses, intuitively discover patterns or errors in large data collections.
In this tutorial we will provide a hands-on demonstration of the essential functionalities of Gephi, based on a real case scenario: the exploration of student networks from the "Facebook100" dataset (Social Structure of Facebook Networks, Amanda L. Traud et al, 2011). The participants will be guided step by step through the complete chain of representation, manipulation, layout, analysis and aesthetics refinements. Particular focus will be put on filters and metrics for the creation of their first visualizations. They will be incited to compare the hypotheses suggested by their own exploration to the results actually published in the academic paper afterwards. They finally will walk away with the practical knowledge enabling them to use Gephi for their own projects. The tutorial is intended for professionals, researchers and graduates who wish to learn how playing during a network exploration can speed up their studies.
Sébastien Heymann is a Ph.D. Candidate in Computer Science at Université Pierre et Marie Curie, France. His research at the ComplexNetworks team focuses on the dynamics of realworld networks. He leads the Gephi project since 2008, and is the administrator of the Gephi Consortium.
Julian Bilcke is a Software Engineer at ISC-PIF (Complex Systems Institute of Paris, France). He is a founder and a developer for the Gephi project since 2008.
Ethical and Legal Issues in Computational Social Science - Lecture 7 in Intro...Lauri Eloranta
Seventh lecture of the course CSS01: Introduction to Computational Social Science at the University of Helsinki, Spring 2015.(http://blogs.helsinki.fi/computationalsocialscience/).
Lecturer: Lauri Eloranta
Questions & Comments: https://twitter.com/laurieloranta
This short set of slides summarizes the characteristics of people who play specific roles in networks. In a social network analysis, people in these roles can be discovered by running mathematical algorithms through the social graphs. But you don't need to be an algorithm to spot some of these people in your networks!
A Perspective on Graph Theory and Network ScienceMarko Rodriguez
The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science.
This is an autobiographical lecture on my life (so far) with graphs/networks.
Introduction to Computational Social Science - Lecture 1Lauri Eloranta
First lecture of the course CSS01: Introduction to Computational Social Science at the University of Helsinki, Spring 2015. (http://blogs.helsinki.fi/computationalsocialscience/).
Lecturer: Lauri Eloranta
Questions & Comments: https://twitter.com/laurieloranta
Social Network Analysis & an Introduction to ToolsPatti Anklam
This presentation was delivered as part of an intense knowledge management curriculum. It covers the basics of network analysis and then goes into the different types of tool that support analyzing networks.
Is network theory the best hope for regulating systemic risk?Kimmo Soramaki
The presentation is organised around three policy questions:
1. How can we measure the systemic importance of a bank?
2. Can regulators promote a safer financial system by affecting its topology?
3. Is it possible to devise early-warning indicators from real-time data?
Social Network Analysis for Competitive IntelligenceAugust Jackson
How can CI teams apply the concepts of social network analysis to gain insight into the capabilities and plans of their competitors? Presented by Jim Richardson and August Jackson in April 2007 at the Society of Competitive Intelligence Professionals annual conference in New York City.
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...guest803e6d
A theoretically-grounded learning feedback tool suite, the Visible Effort (VE) Mediawiki extension, is proposed for optimizing online group learning activities by measuring the amount of equality and the emergence of social structure in groups that participate in Computer-Mediated Collaboration (CMC). Building on social entropy theory, drawn from Shannon’s Mathematical Theory of Communication, VE captures levels of CMC unevenness and group structure and visualizes them on wiki Web pages through background colors, charts, and tabular data. Visual information provides users entropic feedback on how balanced and equitable collaboration is within their online group are, while helping them to maintain it within optimal levels. Finally, we present the theoretical and practical implications of VE and the measures behind it, as well as illustrate VE’s capabilities by describing a quasi-experimental teaching activity (use scenario) in tandem with a detailed discussion of theoretical justification, methodological underpinning, and technological capabilities of the approach.
Applying research methods: Investigating the Many Faces of Digital Visitors &...Lynn Connaway
Connaway, L. S. (2018). Applying research methods: Investigating the Many Faces of Digital Visitors & Residents. Presented at the American University, March 29, 2018, Rome, Italy.
A lefedettségi metrikákat nemcsak a tesztkészlet kiértékelésére lehet használni, hanem arra is, hogy a forráskód alapján olyan teszteseteket származtassuk, amik magas lefedettséget érnek el. Az ilyen technikák hasznos kiegészítői lehetnek a fejlesztői és tesztelői eszköztárnak. Az előadás bemutatja a forráskód alapú tesztbemenet-generáló módszereket és egy konkrét .NET-es egységteszt-generáló megoldás, a Microsoft Pex eszközével kapcsolatos tapasztalatokat.
Nowadays, we are constantly interacting with computers, mobiles and other wearable devices. These interactions leave behind the digital footprint of the user. This data is used with different goals in the so-called Big Data field to predict customer behaviour in marketing and health research. Learning Analytics tackles this challenge in the Technology Enhanced Learning field.
George Siemens defines Learning Analytics as the measurement, collection, analysis and reporting of the data to understand and optimise learning. In this context, we find a variety of studies that process the data different. Some studies implement complex algorithms and display the outcome to the user. Others rely on simpler approaches to process the data but enabling the user to explore the data with understandable, comprehensive and usable visualisations. Users can draw conclusions by their own and, with this information, steer their own learning process. This thesis is contextualised in the latter and intends to help students to become autonomous and lead their own educational process.
This dissertation presents the work in the scope of four research questions: 1) RQ1 - What characteristics of learning activities can be visualised usefully for learners?; 2) RQ2 - What characteristics of learning activities can be visualised usefully for teachers?; 3) RQ3 - What are the affordances of and user problems with tracking data automatically and manually?; and 4) RQ4 - What are the key components of a simple and flexible architecture to collect, store and manage learning activity?.
The exploration of these research questions include the deployment of: 1) three different learning dashboard designs deployed in real courses with 128 students participating in the evaluations; 2) the analysis of two Massive Open Online Courses (MOOCs) with 56876 enrolled students; and 3) the deployment of an architecture in two real case studies, including a European project with more than 15 scheduled pilots.
Manual and automatic trackers have benefits and drawbacks. For example, manual trackers respect the user privacy in blended learning courses but the data provided by the students is not trusted by their fellow students. Automatic trackers are more accurate, but they do not track the activity outside of the computer, and, therefore, do not provide the complete picture that students demand.
This research also identifies three components to deploy a simple and flexible architecture to collect data in open learning environments: 1) a set of simple services to push and pull the learning traces; 2) a simple data schema to ensure completeness and findability of the data; and 3) independent components to collect the learning activity.
Languages and frameworks for specifying test artifactsZoltan Micskei
Presentation of a PhD dissertation with the following contributions: (i) a robustness test framework for HA middleware systems, (ii) analysis of the semantics of UML 2 Sequence Diagrams, (iii) definition of a test framework and test language (TERMOS) for mobile computing systems.
How can we increase engagement in teaching and learning activities by encourage the development of teaching presence in the Community of Inquiry model framework.
Balanced Diversity A Portfolio Approach to Organisational Change (2012)Karen Ferris
This presentation will explore what we mean by cultural change; the challenges that we face when trying to embed a change into our organisations.
It proposes the adoption of a new and innovative framework which provides a portfolio approach to embedding change.
This provides a balanced approach using a wide range of practices. It is the adoption of a diverse set of practices within a balanced portfolio that is required to achieve sufficient penetration and traction that will ensure successful organisational change.
The framework can be used for strategic, tactical and operational changes of all sizes and complexity. It can be used for any type of change but we will look at its application for IT Service Management and some practical steps you can take back in the workplace to apply the framework and achieve successful change.
Contextual Recommendation of Social Updates, a tag-based frameworkAdrien Joly
How to cope with information overload?
In this presentation (and the corresponding paper), we propose a framework to improve the relevance of awareness information about people and subjects, by adapting recommendation techniques to real-time web data, in order to reduce information overload. The novelty of our approach relies on the use of contextual information about people's current activities to rank social updates which they are following on Social Networking Services and other collaborative software. The two hypothesis that we are supporting in this paper are: (i) a social update shared by person X is relevant to another person Y if the current context of Y is similar to X's context at time of sharing; and (ii) in a web-browsing session, a reliable current context of a user can be processed using metadata of web documents accessed by the user. We discuss the validity of these hypothesis by analyzing their results on experimental data.
Presented by Adrien Joly, on the 28/08/2010, at the Active Media Technology (AMT) conference, Toronto, Ontario, Canada.
Workspace Awareness without Overload: Contextual Filtering of Social Interact...Adrien Joly
Adrien Joly's PhD work in progress on Enterprise Ambient Awareness, presented 19/07/2009 at Smart Offices and Other Workspaces, Workshop of the Intelligent Environments 2009 conference, Barcelona, Spain.
Workshop by Rebecca Galley & Nick Freear at the Staff & Educational Development Association (SEDA) annual conference, 17-18 November 2011. We talked about the open-source CloudEngine project, and it's relation to the JISC OULDI project.
ICSME 2016 keynote: An ecosystemic and socio-technical view on software maint...Tom Mens
These are the slides of my ICSME 2016 keynote, presented on 5 October 2016 in Raleigh, North Carolina. I focus on the difficulties of maintaining and evolving software ecosystems, large collections of interacting software components that are maintained by a large and active community of contributors and that evolve together in the same environment. Software ecosystems are becoming ubiquitous due to the omnipresence of open source software. I present several problems that arise during maintenance and evolution of software ecosystems, and I argue how some of these challenges should be addressed by adopting a socio-technical view and by relying on a multidisciplinary and mixed methods research approach. I illustrate this with examples of social network analysis, complex systems research, ecological biodiversity, and survival analysis.
Web Accessibility 3.0: Learning From The Past, Planning For The Futurelisbk
Slides for a talk on "Web Accessibility 3.0: Learning From The Past, Planning For The Future" given at the ADDW08 conference.
See http://www.ukoln.ac.uk/web-focus/events/conferences/addw08/
Towards the Design of Intelligible Object-based Applications for the Web of T...Pierrick Thébault
Presentation given at the second international workshop on the Web of Things (in conjunction with the ninth international conference on pervasive computing, san francisco, usa, june 2011).
More details on http://www.wothings.com.
Wall-sized poster we used to exhibit Social Campus at Cornell Tech's Open Studio event. Social Campus is an iPhone event-networking + recommendations + social network iPhone app created in collaboration with Cornell Tech. It includes a context-aware platform that transforms the campus to a place that fosters collaboration and connects people from academia, industry, and the public. It suggests people/events on campus that match your interests, as well as assists networking at on-campus events.
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
The Future for Educational Resource Repositories in a Web 2.0 Worldlisbk
Slides for a talk on "The Future for Educational Resource Repositories in a Web 2.0 World" given by Brian Kelly, UKOLN at an Edspaces workshop held at the University of Southampton on 4 November 2009.
See http://www.ukoln.ac.uk/web-focus/events/workshops/edspace-2009/
Introductory presentation given at Future Learning Landscape Workshop held at EC-TEL 2009. Presents some introductory elements about the state of research in pervasive learning, Web 2.0/Social Software and Semantic Web/Linked Data before discussing convergence
Similar to PhD Defense - A Context Management Framework based on Wisdom of Crowds for Social Awareness Applications (20)
Written for a seminar at Universiteit Twente (Netherlands) in March 2009, this presentation by Adrien Joly (Alcatel-Lucent Bell Labs France) introduces approaches for improved enterprise communication and collaboration, which motivates a convergent framework of real-time contextual notifications based on employees' work context. The framework is presented and current research issues (work in progress) are introduced.
Context-Awareness, the missing block of Social NetworkingAdrien Joly
Social Networking Sites (such as Facebook, Linkedin or Twitter) have brought new communication and interaction opportunities. In this presentation, after introducing the communication features of most popular Social Networking Sites, we propose to leverage Context Awareness (including location-awareness, but not only) in order to trigger more communication from these sites while not requiring their users to spend more time managing their network.
Context-Awareness, the missing block of Social Networking
PhD Defense - A Context Management Framework based on Wisdom of Crowds for Social Awareness Applications
1. A Context Management Framework based on Wisdom of Crowds for Social Awareness applications Adrien JOLY PhD Candidate, supervisor: Prof. Pierre MARET, LaHC CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205
2. Un cadre de Gestion de Contextes fondé sur l’Intelligence Collective pour améliorer l’efficacité des applications de Communication Sociale Adrien JOLY CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205 Encadré par: Prof. Pierre MARET (LaHC), Johann Daigremont (ALBLF)
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22. Context Approach Framework Evaluation Conclusion Context Aggregation and Filtering process Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
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24. Context Approach Framework Evaluation Conclusion How to synthesize the contextual tag cloud from web browsing ? The user opens a web page…
25. Context Approach Framework Evaluation Conclusion How to synthesize the contextual tag cloud from web browsing ? Low level and static author description Automatic content analysis Mining semantic concepts from content People-entered tags (wisdom of crowds) 1) URL is sent to the Context Aggregator 2) Content is analyzed by enhancers (including web services)
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31. Context Approach Framework Evaluation Conclusion Context Aggregation and Filtering process –- in the enterprise Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
32. Context Approach Framework Evaluation Conclusion Implementation Firefox extension (Javascript) to track web browsing Windows daemon (C++) to track opened PDF documents Lightweight HTTP Server (Java) + 5 tag extractors (Java) incl. 2 web service wrappers Jetty-based HTTP Server (Java) DWR for server-push (Java) Off-line scripts (Java+shell) Firefox sidebar (HTML+Javascript) Mobile application (Java for android) Aggregator Sniffers Notifier Filter Social updates User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
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36. Context Approach Framework Evaluation Conclusion From browsing activity to social matching Temporal indexing period = 10 mn. Common tags: JAVA, DEV Common tags: TRAVEL Recommend u5’s social update to u1 Recommend u3’s social update to u7
37. Context Approach Framework Evaluation Conclusion 1. Relevance of social updates based on contextual similarity Matching
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41. Context Approach Framework Evaluation Conclusion 2. Relevance of social updates to the context of their posting
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43. Context Approach Framework Evaluation Conclusion 3. Differences between context from virtual and social sensors Combining virtual and social sensors: good compromise between quantity and quality of matches 280k Number of matches 40k 170k 130k 70k 10k Low precision matches High precision matches