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AFEL - Analytics For Everyday Learning

Deliverables

Detection and Enrichment of Learning Patterns/Notions v.1

This deliverable will describe an initial version of the results and methods originating from the detection and enrichment work in WP2, where the key aim is to identify learning-related notions and patterns in data produced in WP1, WP2 and WP4. That may include automated means of enriching data as well as additional experimental work to identify or verify patterns/notions of learning, collaboration or knowledge production.

Description of the available social environments and data

This document will specify and describe the social spaces that will be studied in the use case, that is: a) identify and characterise the set of GNOSS-Didactalia communities for the analysis, as main environments of the use case, b) define which other additional potential environments will be employed for the use case, establishing the strategy and methods to obtain their data, perform the integration and evaluate the results. It will also identify which data will be collected from the activity and interactions of the users in the platforms, for their use in WP1, WP2, WP3 and WP4.

Report on the analysis of handling complexity

This deliverable will present a method and results of using the data from the previous three workpackages and from T4.2 in order to analyse how communities deal with complexity, through filtering out certain pieces of information in order to be able to handle those few influences which that system permits.

Specification of data to be collected

Report on the data that will be extracted from every source (data about users’ activity, how they behave, how they interact with each other and with contents, etc.), that could provide information about learning activities.

Further exploitation plan

Based on the experience gained in carrying out in the Integration of the analytic tools and models (Tasks T5.3) and the addition to the GNOSS commercial offering (T6.4) we will here investigate other possible channels of exploitation, in the form of other platforms where the tools and models of the project can be integrated. Selection of the most promising ones. The results will then be incorporated into a further exploitation plan.

Development and evaluation of ontological and stochastic methods for recognising and classifying learning activities

Description of a method employing an ontological approach to data capture, through integrating the previous data extraction and feature engineering activities with the enrichment provided in WP2 and Markov decision model-based approaches to aligning them with the model of WP4.

Report on the analysis of learning & collaboration

This deliverable will describe methods using the data retrieved and processed in workpackages 1-3 to analyse how knowledge construction in this online social environment occurs, at the community level as well as the individual level.

Report on the analysis of self-organisation

This deliverable will describe a method and the results of using data from the previous three workpackages and from T4.1 to analyse how learning communities maintain themselves by taking up those aspects of communication from the environment that are relevant for its continuance.

Conceptual Framework of Visual analytics of conflicts, problems and barriers

This deliverable introduces a conceptual framework describing visual analytics methods for identifying conflicts, problems and barriers which hinder learning processes in online social environments. An observer (administrator) shall be empowered to make decisions for improving the learning environment and learning experience.

Report describing the analysis of the constitution of meaning

This deliverable will describe methods and results using the data from the previous three workpackages and from T4.3 in order to analyse how systems select certain parts of the irritations and stimuli from outside and transform them into meaningful information.

Integrated model of informal learning in social spaces and evaluation

This deliverable will describe the lessons learnt and an integrated view from the work achieved on different aspects of the analyses of learning activities, communities and complexity in online social (learning) platforms in WP4.

First report on dissemination activities

First report on dissemination activities based on the communication and dissemination targets. Up-date and adaptation of the communication and dissemination plan, if needed.

Final report on exploitation plan and activities

Final report on exploitation plan and activities

Dissemination plan

Set up of a targeted communication and dissemination plan for the project. An essential part of it is the clear determination of communication and dissemination objectives, the identification of relevant target groups and events as well as the development of a target-group-oriented communication strategy.

First evaluation of the adoption and benefit of analytics in social environments

This report will evaluate the use of learning analytic tools (through AFEL tools) in social environments, with main focus in the analysis of their application in GNOSS-Didactalia communities, but also in other online social (learning) platforms that will be defined in D5.1. This first evaluation will be carried out with intermediary data and tools.

Detection and Enrichment of Learning Patterns/Notions v.2

This deliverable describes the second version of D2.3.1 and will describe the refined methods and results for detection and enrichment of learning patterns/notions, specifically considering visual analytics approaches from WP3.

Evaluation results for visual analytics tools

This deliverable provides results on gathered experiences and performed evaluations of the developed visual analytics tools and methods. The results will include qualitative and quantitative analyses evaluating the contribution of developed methods in gaining new insights that aid informal learning.

Final evaluation of the adoption and benefit of analytics in social environments

This deliverable consists of the second and final report that evaluates the application of learning analytics in social environments, with main focus in the analysis of their application in GNOSS-Didactalia communities, but also in other online social (learning) platforms that will be defined in D5.1.This report will be carried out on final results of the project and will take into account the evaluations performed in WP3 (D3.7) and WP4 (D4.5).

Data management, final report

Final version of the data management report.

Data Analytics & Entity Linking for Learning Analytics

This deliverable will describe analytics, enrichment and linking approaches for the data and learning analytics scenarios in the project. This includes methods for analysing and consolidating data produced in WP1 - by automated means as well as through Web-scale crowdsourcing - as well as the derivation of novel analytical approaches for extracting relevant insights, for instance, wrt theories and models produced WP4.

Conceptual Framework of Visual analytics of Communities

This deliverable introduces a conceptual framework describing visual analytics methods for gaining understanding of informal learning processes in online social environments. The focus is on understanding communities and patterns in social learning processes, including analysis of the evolution of learning activity streams, and delivery of a personalized visual environmet enabling user to make progress depending on explicit and implicit (derived) preferences.

Feature definitions and extraction methods

Description of the first layer of data processing, researching the features in the raw data extracted, to obtain information that can be meaningfully processed for analysis and modelling.

Second report on dissemination activities

Final report on dissemination activities based on the communication and dissemination targets.

AFEL public online community and external communication tools

A dedicated, public community on GNOSS will be setup to connect with interested parties. Set up of the AFEL project website, as well as of social media (twitter feed, etc.) to connect to the relevant communities.

Web of GNOSS products updated with AFEL tools offer

The AFEL tools integrated into the GNOSS platform will be included in the web of GNOSS products as part of its commercial offering.

AFEL-based API, applications and solutions for online social platforms

Development of prototype applications with potential for commercial applications after the project’s end. This includes application for informal learning of generic social networking platform such as Facebook or LinkedIn, as well as the potential development of more dedicated solutions for social/informal learning to be integrated within schools’/universities’ ICT environments (e.g. SocialLearn - http://sociallearn.open.ac.uk and LearnWeb). This will also include offering an open source development API for the tools and techniques developed in the project, as a simplified version of the technical platform applied on GNOSS and usable to develop applications of other online social systems.

Large-Scale Dataset for (Social) Learning Analytics, Release 3

This deliverable describes the second version of the AFEL datasets and will contain an expanded, enriched and restructured version of D2.4.

Large-Scale Dataset for (Social) Learning Analytics, Release 2

This deliverable describes the second version of the AFEL datasets and will contain an expanded, enriched and restructured version of D2.2.

Complete data extraction and management infrastructure and evaluation

This deliverable presents the second and completed version of the data extraction and management infrastructure of the project.

Ontological models of learning activities

An ontological framework for the data-modelling definition of learning activities, in such a way that they can be recognised, and to a certain extent classified, from the data obtained from social media.

Integrated feature extraction for analytics and evaluations

This prototype exploits the feedback loop between the later analytics, enrichment and modelling tasks of the project to identify base requirements for the identifications of learning activities, and address them through employing state of the art clustering, natural language processing and data re-factoring techniques.

Base data management infrastructure and core data model

Data extraction and management infrastructure to collect data from online social environments and make them available to the rest of the project. This includes the core data model of the project (integrating existing models into a linked data-compliant vocabulary), creating extractors for specific sources of data such as the logs of GNOSS, Facebook’s activity streams or LinkedIn skills and education APIs, and deploying a data management platform consisting of a triple store and a data endpoint for supporting convenient use by other processes in the project.

Large-Scale Dataset for (Social) Learning Analytics, Release 1

The first version of the AFEL dataset will consist primarily of data collected as part of data extraction and crawling activities in WP1 and WP2. Data will be enriched and expanded throughout later iterations of the dataset.

Application of analytics tools and models in additional online social platforms

Generic tools developed with the GNOSS platform as a primary testbed will be extracted and tested on other social platforms and made available as reusable components.

Publications

Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms

Author(s): Dominik Kowald, Elisabeth Lex
Published in: 2017

Fine Grained Citation Span for References in Wikipedia

Author(s): Besnik Fetahu, Katja Markert, Avishek Anand
Published in: 2017

Tags, Titles or Q&As? - Choosing Content Descriptors for Visual Recommender Systems

Author(s): Belgin Mutlu, Eduardo Veas, Christoph Trattner
Published in: Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT '17, 2017, Page(s) 265-274
DOI: 10.1145/3078714.3078741

Predicting User Knowledge Gain in Informational Search Sessions

Author(s): Ran Yu, Ujwal Gadiraju, Peter Holtz, Markus Rokicki, Philipp Kemkes, Stefan Dietze
Published in: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18, 2018, Page(s) 75-84
DOI: 10.1145/3209978.3210064

Clarity is a Worthwhile Quality - On the Role of Task Clarity in Microtask Crowdsourcing

Author(s): Ujwal Gadiraju, Jie Yang, Alessandro Bozzon
Published in: Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT '17, 2017, Page(s) 5-14
DOI: 10.1145/3078714.3078715

can bots be better learners than humans?

Author(s): Wassim Derguech, Mathieu d’Aquin
Published in: Proceedings of the Re-coding Black Mirror 2017 Workshop, 2017

FuseM: Query-Centric Data Fusion on Structured Web Markup

Author(s): Ran Yu, Ujwal Gadiraju, Besnik Fetahu, Stefan Dietze
Published in: 2017 IEEE 33rd International Conference on Data Engineering (ICDE), 2017, Page(s) 179-182
DOI: 10.1109/icde.2017.69

Analyzing Knowledge Gain of Users in Informational Search Sessions on the Web

Author(s): Ujwal Gadiraju, Ran Yu, Stefan Dietze, Peter Holtz
Published in: Proceedings of the 2018 Conference on Human Information Interaction&Retrieval - CHIIR '18, 2018, Page(s) 2-11
DOI: 10.1145/3176349.3176381

Supporting virtual integration of Linked Data with just-in-time query recompilation

Author(s): Alessandro Adamou, Mathieu d'Aquin, Carlo Allocca, Enrico Motta
Published in: Proceedings of the 13th International Conference on Semantic Systems - Semantics2017, 2017, Page(s) 112-119
DOI: 10.1145/3132218.3132227

AFEL: Towards Measuring Online Activities Contributions to Self-directed Learning

Author(s): Mathieu D'Aquin, Alessandro Adamou, Stefan Dietze, Besnik Fetahu, Ujwal Gadiraju, Ilire Hasani-Mavriqi, Peter Holtz, Joachim Kimmerle, Dominik Kowald, Elisabeth Lex, Susana Lopez Sola, Ricardo Maturana, Vedran Sabol, Pinelopi Troullinou, Eduardo Veas
Published in: Proceedings of the 7th Workshop on Awareness and Reflection in Technology Enhanced Learning, 2017

Improving learning through achievement priming in crowdsourced information finding microtasks

Author(s): Ujwal Gadiraju, Stefan Dietze
Published in: Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17, 2017, Page(s) 105-114
DOI: 10.1145/3027385.3027402

Inferring Missing Categorical Information in Noisy and Sparse Web Markup

Author(s): Nicolas Tempelmeier, Elena Demidova, Stefan Dietze
Published in: Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18, 2018, Page(s) 1297-1306
DOI: 10.1145/3178876.3186028

AFEL - Analytics for Everyday Learning

Author(s): Mathieu d'Aquin, Dominik Kowald, Angela Fessl, Elisabeth Lex, Stefan Thalmann
Published in: Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018, Page(s) 439-440
DOI: 10.1145/3184558.3186206

Assessing the Readability of Policy Documents - The Case of Terms of Use of Online Services

Author(s): Wassim Derguech, Syeda Sana e Zainab, Mathieu D'Aquin
Published in: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance - ICEGOV '18, 2018, Page(s) 247-256
DOI: 10.1145/3209415.3209498

Finding traces of self-regulated learning in activity streams

Author(s): Analía Cicchinelli, Eduardo Veas, Abelardo Pardo, Viktoria Pammer-Schindler, Angela Fessl, Carla Barreiros, Stefanie Lindstädt
Published in: Proceedings of the 8th International Conference on Learning Analytics and Knowledge - LAK '18, 2018, Page(s) 191-200
DOI: 10.1145/3170358.3170381

The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations - An Online Study

Author(s): Dominik Kowald, Paul Seitlinger, Tobias Ley, Elisabeth Lex
Published in: Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18, 2018, Page(s) 1-2
DOI: 10.1145/3184558.3186899

Trust-based collaborative filtering - tackling the cold start problem using regular equivalence

Author(s): Tomislav Duricic, Emanuel Lacic, Dominik Kowald, Elisabeth Lex
Published in: Proceedings of the 12th ACM Conference on Recommender Systems - RecSys '18, 2018, Page(s) 446-450
DOI: 10.1145/3240323.3240404

Detecting, Understanding and Supporting Everyday Learning in Web Search

Author(s): Ran Yu, Ujwal Gadiraju, Stefan Dietze
Published in: LILE 2018, 2018

Current Challenges for Studying Search as Learning Processes

Author(s): Anett Hoppe, Peter Holtz, Yvonne Kammerer, Ran Yu, Stefan Dietze, Ralph Ewerth
Published in: LILE 2018, 2018

Wikipedia article measures in relation to content characteristics of lead sections.

Author(s): Seren Yenikent, Brett Buttliere, Besnik Fetahu, Joachim Kimmerle
Published in: LILE 2018, 2018

Real-time Event-based News Suggestion for Wikipedia Pages from News Streams.

Author(s): Lijun Lyu and Besnik Fetahu
Published in: WikiWorkshop 2018, 2018

Detecting Biased Statements in Wikipedia.

Author(s): Christoph Hube and Besnik Fetahu
Published in: WikiWorkshop 2018, 2018

AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments

Author(s): Kowald, D., Lacic, E., Theiler, D., Lex, E.
Published in: Social Interaction-Based Recommender Systems (SIR'2018) Workshop, 2018

Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations

Author(s): Emanuel Lacic, Dominik Kowald, Elisabeth Lex
Published in: International Workshop on Entity Retrieval (EYRE'2018) Workshop, 2018

Evaluating the AFEL learning tools: Didactalia users’ experiences with personalized recommendations and interactive visualizations.

Author(s): Seren Yenikent, Peter Holtz, Stefan Thalmann, Mathieu D’Aquin, Joachim Kimmerle
Published in: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018

Analytics for Everyday Learning from two Perspectives: Knowledge Workers and Teachers.

Author(s): Angela Fessl, Dominik Kowald, Susana López Sola, Ana Moreno, Ricardo Alonso Maturana, Stefan Thalmann
Published in: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018

Towards a Learning Dashboard for Community Visualization

Author(s): Belgin Mutlu, Ilija Simic, Analia Cicchinelli, Vedran Sabol, Eduardo Veas
Published in: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018

Detection of Online Learning Activity Scopes

Author(s): Syeda Sana E. Zainab, Mathieu D'Aquin
Published in: Proceedings of the 1st Workshop on Analytics for Everyday Learning, 2018

Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL

Author(s): Simone Kopeinik, Dominik Kowald, Elisabeth Lex
Published in: Which Algorithms Suit Which Learning Environments? A Comparative Study of Recommender Systems in TEL, Issue 11th European Conference on Technology Enhanced Learning, EC-TEL 2016, Lyon, France, September 13-16, 2016, Proceedings, 2016, Page(s) 124-138
DOI: 10.1007/978-3-319-45153-4_10

Semantic Stability in Wikipedia

Author(s): Darko Stanisavljevic, Ilire Hasani-Mavriqi, Elisabeth Lex, Markus Strohmaier, Denis Helic
Published in: Complex Networks & Their Applications V. COMPLEX NETWORKS 2016 2016., Issue Studies in Computational Intelligence, vol 693, 2017, Page(s) 379-390
DOI: 10.1007/978-3-319-50901-3_31

Finding News Citations for Wikipedia

Author(s): Besnik Fetahu, Katja Markert, Wolfgang Nejdl, Avishek Anand
Published in: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16, 2016, Page(s) 337-346
DOI: 10.1145/2983323.2983808

Unlock the Stock: User Topic Modeling for Stock Market Analysis

Author(s): Patrick Siehndel and Ujwal Gadiraju, L3S Research Center, Leibniz Universität Hannover, Germany
Published in: Published in the Workshop Proceedings of the EDBT/ICDT 2016 Joint Conference (March 15, 2016, Bordeaux, France) on CEUR-WS.org (ISSN 1613-0073), Issue EDBT/ICDT Workshops 2016, 2016, Page(s) 1558, ISSN 1613-0073

It's getting crowded! - how to use crowdsourcing effectively for web science research

Author(s): Ujwal Gadiraju, Gianluca Demartini, Djellel Eddine Difallah, Michele Catasta
Published in: Proceedings of the 8th ACM Conference on Web Science - WebSci '16, 2016, Page(s) 11-11
DOI: 10.1145/2908131.2908140

Estimating domain specificity for effective crowdsourcing of link prediction and schema mapping

Author(s): Ujwal Gadiraju, Patrick Siehndel, Stefan Dietze
Published in: Proceedings of the 8th ACM Conference on Web Science - WebSci '16, 2016, Page(s) 323-324
DOI: 10.1145/2908131.2908209

Where the Event Lies - Predicting Event Occurrence in Textual Documents

Author(s): Andrea Ceroni, Ujwal Gadiraju, Jan Matschke, Simon Wingert, Marco Fisichella
Published in: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16, 2016, Page(s) 1157-1160
DOI: 10.1145/2911451.2911452

Adaptive Focused Crawling of Linked Data

Author(s): Ran Yu, Ujwal Gadiraju, Besnik Fetahu, Stefan Dietze
Published in: Web Information Systems Engineering – WISE 2015. Lecture Notes in Computer Science, Issue vol 9418, 2015, Page(s) 554-569
DOI: 10.1007/978-3-319-26190-4_37

A Survey on Challenges for Entity Retrieval in Web Markup Data

Author(s): Ran Yu, Besnik Fetahu, Ujwal Gadiraju and Stefan Dietze
Published in: Proceedings of the ISWC 2016 Posters & Demonstrations Track co-located with 15th International Seman, Issue Vol-1690, 2016, Page(s) paper70

Towards Entity Summarisation on Structured Web Markup

Author(s): Ran Yu, Ujwal Gadiraju, Xiaofei Zhu, Besnik Fetahu, Stefan Dietze
Published in: The Semantic Web. ESWC 2016. Lecture Notes in Computer Science, Issue vol 9989, 2016, Page(s) 69-73
DOI: 10.1007/978-3-319-47602-5_15

Towards Embedded Markup of Learning Resources on the Web - An Initial Quantitative Analysis of LRMI Terms Usage

Author(s): Davide Taibi, Stefan Dietze
Published in: Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion, 2016, Page(s) 513-517
DOI: 10.1145/2872518.2890464

Beyond Established Knowledge Graphs-Recommending Web Datasets for Data Linking

Author(s): Mohamed Ben Ellefi, Zohra Bellahsene, Stefan Dietze, Konstantin Todorov
Published in: eb Engineering. ICWE 2016. Lecture Notes in Computer Science, Issue vol 9671, 2016, Page(s) 262-279
DOI: 10.1007/978-3-319-38791-8_15

Supporting collaborative learning with tag recommendations - a real-world study in an inquiry-based classroom project

Author(s): Simone Kopeinik, Elisabeth Lex, Paul Seitlinger, Dietrich Albert, Tobias Ley
Published in: Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17, 2017, Page(s) 409-418
DOI: 10.1145/3027385.3027421

The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems

Author(s): Dominik Kowald, Simone Kopeinik, Elisabeth Lex
Published in: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization - UMAP '17, 2017, Page(s) 23-28
DOI: 10.1145/3099023.3099069

Temporal Effects on Hashtag Reuse in Twitter - A Cognitive-Inspired Hashtag Recommendation Approach

Author(s): Dominik Kowald, Subhash Chandra Pujari, Elisabeth Lex
Published in: Proceedings of the 26th International Conference on World Wide Web - WWW '17, 2017, Page(s) 1401-1410
DOI: 10.1145/3038912.3052605

Analysing and Improving Embedded Markup of Learning Resources on the Web

Author(s): Stefan Dietze, Davide Taibi, Ran Yu, Phil Barker, Mathieu d'Aquin
Published in: Proceeding WWW '17 Companion Proceedings of the 26th International Conference on World Wide Web Companion, 2017, Page(s) Pages 283-292
DOI: 10.1145/3041021.3054160

Measuring Accuracy of Triples in Knowledge Graphs

Author(s): Shuangyan Liu, Mathieu d’Aquin, Enrico Motta
Published in: Language, Data, and Knowledge. LDK 2017. Lecture Notes in Computer Science, Issue vol 10318, 2017, Page(s) 343-357
DOI: 10.1007/978-3-319-59888-8_29

Unsupervised learning for understanding student achievement in a distance learning setting

Author(s): Shuangyan Liu, Mathieu d'Aquin
Published in: 2017 IEEE Global Engineering Education Conference (EDUCON), 2017, Page(s) 1373-1377
DOI: 10.1109/EDUCON.2017.7943026

Dataset Recommendation for Data Linking: An Intensional Approach

Author(s): Mohamed Ben Ellefi, Zohra Bellahsene, Stefan Dietze, Konstantin Todorov
Published in: he Semantic Web. Latest Advances and New Domains. ESWC 2016. Lecture Notes in Computer Science, Issue vol 9678, 2016, Page(s) 36-51
DOI: 10.1007/978-3-319-34129-3_3

SPARQL Query Recommendations by Example

Author(s): Carlo Allocca, Alessandro Adamou, Mathieu d’Aquin, Enrico Motta
Published in: The Semantic Web. ESWC 2016. Lecture Notes in Computer Science, Issue vol 9989, 2016, Page(s) 128-133
DOI: 10.1007/978-3-319-47602-5_26

Using Worker Self-Assessments for Competence-Based Pre-Selection in Crowdsourcing Microtasks

Author(s): Ujwal Gadiraju, Besnik Fetahu, Ricardo Kawase, Patrick Siehndel, Stefan Dietze
Published in: ACM Transactions on Computer-Human Interaction, Issue 24/4, 2017, Page(s) 1-26, ISSN 1073-0516
DOI: 10.1145/3119930

The Impact of Topic Characteristics and Threat on Willingness to Engage with Wikipedia Articles: Insights from Laboratory Experiments

Author(s): Seren Yenikent, Peter Holtz, Joachim Kimmerle
Published in: Frontiers in Psychology, Issue 8, 2017, ISSN 1664-1078
DOI: 10.3389/fpsyg.2017.01960

Modus Operandi of Crowd Workers

Author(s): Ujwal Gadiraju, Alessandro Checco, Neha Gupta, Gianluca Demartini
Published in: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Issue 1/3, 2017, Page(s) 1-29, ISSN 2474-9567
DOI: 10.1145/3130914

VizRec

Author(s): Belgin Mutlu, Eduardo Veas, Christoph Trattner
Published in: ACM Transactions on Interactive Intelligent Systems, Issue 6/4, 2016, Page(s) 1-39, ISSN 2160-6455
DOI: 10.1145/2983923

KnowMore - Knowledge Base Augmentation with Structured Web Markup

Author(s): Ran Yu Ujwal Gadiraju Besnik Fetahu Oliver Lehmberg Dominique Ritze Stefan Dietze
Published in: Semantic Web Journal, 2017, ISSN 1570-0844

Using big data techniques for measuring productive friction in mass collaboration online environments

Author(s): Peter Holtz, Joachim Kimmerle, Ulrike Cress
Published in: International Journal of Computer-Supported Collaborative Learning, Issue 13/4, 2018, Page(s) 439-456, ISSN 1556-1607
DOI: 10.1007/s11412-018-9285-y

Consensus dynamics in online collaboration systems

Author(s): Ilire Hasani-Mavriqi, Dominik Kowald, Denis Helic, Elisabeth Lex
Published in: Computational Social Networks, Issue 5/1, 2018, ISSN 2197-4314
DOI: 10.1186/s40649-018-0050-1

The triple-filter bubble: Using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers

Author(s): Daniel Geschke, Jan Lorenz, Peter Holtz
Published in: British Journal of Social Psychology, Issue 58/1, 2019, Page(s) 129-149, ISSN 0144-6665
DOI: 10.1111/bjso.12286

Effects of Contributor Experience on the Quality of Health-Related Wikipedia Articles

Author(s): Peter Holtz, Besnik Fetahu, Joachim Kimmerle
Published in: Journal of Medical Internet Research, Issue 20/5, 2018, Page(s) e171, ISSN 1438-8871
DOI: 10.2196/jmir.9683

The influence of social status and network structure on consensus building in collaboration networks

Author(s): Ilire Hasani-Mavriqi, Florian Geigl, Subhash Chandra Pujari, Elisabeth Lex, Denis Helic
Published in: Social Network Analysis and Mining, Issue 6/1, 2016, Page(s) Sudies in Computational Intelligence, ISSN 1869-5450
DOI: 10.1007/s13278-016-0389-y

The Epistemology of Intelligent Semantic Web Systems

Author(s): Mathieu d'Aquin, Enrico Motta
Published in: Synthesis Lectures on the Semantic Web: Theory and Technology, Issue 6/1, 2016, Page(s) 1-88, ISSN 2160-4711
DOI: 10.2200/S00708ED1V01Y201603WBE014

How Popper’s ‘Three Worlds Theory’ Resembles Moscovici’s ‘Social Representations Theory’ But Why Moscovici’s Social Psychology of Science Still Differs From Popper’s Critical Approach

Author(s): Peter HOLTZ, Leibniz-Institut für Wissensmedien IWM (Knowledge Media Research Center) – Knowledge, Construction Lab, Tübingen, Germany.
Published in: Papers on Social Representations, Issue Volume 25, Issue 1, 2016, Page(s) 13.1-13.24, ISSN 1021-5573

A productive clash of perspectives? The interplay between articles’ and authors’ perspectives and their impact on Wikipedia edits in a controversial domain

Author(s): Jens Jirschitzka, Joachim Kimmerle, Iassen Halatchliyski, Julia Hancke, Detmar Meurers, Ulrike Cress
Published in: PLOS ONE, Issue 12/6, 2017, Page(s) e0178985, ISSN 1932-6203
DOI: 10.1371/journal.pone.0178985

Improving Collaborative Filtering Using a Cognitive Model of Human Category Learning

Author(s): Simone Kopeinik
Published in: Journal of Web Science, Issue 2/1, 2016, Page(s) 45-61, ISSN 2332-4031
DOI: 10.1561/106.00000007

Facilitating Scientometrics in Learning Analytics and Educational Data Mining – the LAK Dataset

Author(s): Stefan Dietze, Davide Taibi, Mathieu d’Aquin
Published in: Semantic Web, Issue 8/3, 2016, Page(s) 395-403, ISSN 1570-0844
DOI: 10.3233/SW-150201

"""Make hay while the crowd shines: towards effective crowdsourcing on the web"" by Ujwal Gadiraju, with Prateek Jain as coordinator"

Author(s): Ujwal Gadiraju
Published in: ACM SIGWEB Newsletter, Issue Summer, 2016, Page(s) 1-1, ISSN 1931-1745
DOI: 10.1145/2956573.2956576

Improving Reliability of Crowdsourced Results by Detecting Crowd Workers with Multiple Identities

Author(s): Ujwal Gadiraju, Ricardo Kawase
Published in: Web Engineering, Issue 10360, 2017, Page(s) 190-205
DOI: 10.1007/978-3-319-60131-1_11

On the Use of Linked Open Data in Education: Current and Future Practices

Author(s): Mathieu d’Aquin
Published in: Lecture Notes in Computer Science book series, Issue LNCS, volume 9500, 2016, Page(s) 3-15
DOI: 10.1007/978-3-319-30493-9_1

Educational Linked Data on the Web - Exploring and Analysing the Scope and Coverage

Author(s): Davide Taibi, Giovanni Fulantelli, Stefan Dietze, Besnik Fetahu
Published in: Open Data for Education. Lecture Notes in Computer Science, Issue vol 9500, 2016, Page(s) 16-37, ISSN 0302-9743
DOI: 10.1007/978-3-319-30493-9_2

Open Data for Education

Author(s): Dmitry Mouromtsev, Mathieu d’Aquin
Published in: Lecture Notes in Computer Science, 2016
DOI: 10.1007/978-3-319-30493-9