Dr. Mark Kibanov

Hinweis: Dr. Mark Kibanov ist seit dem 31.05.2018 nicht mehr im Fachgebiet beschäftigt.

Email: kibanov@cs.uni-kassel.de

Research

My research is focused on the data mining algorithms for social networks. Further topics of interest include Software Engineering and IT-Management.

Services

Reviewer

• ACM Transactions on Social Computing
• Elsevier Journal Physica A: Statistical Mechanics and its Applications

PC Member

• 7th International Workshop on Modeling Social Media – Behavioral Analytics in Social Media, Big Data and the Web, April 12th, 2016, Montreal, Canada
• 6th International Workshop on Mining Ubiquitous and Social Environments (MUSE), September 7th, 2015, Porto, Portugal
• 6th International Workshop on Modeling Social Media – Behavioral Analytics in Social Media, Big Data and the Web, May 19th, 2015, Florence, Italy
• 5th International Workshop on Mining Ubiquitous and Social Environments (MUSE), September 15th, 2014, Nancy, France

Subreviewer

• European Conference On Machine Learning and Principles and Practice of Knowledge Discovery, ECML PKDD 2017, September 18th – 22nd, 2017, Skopje, Macedonia
• 25th International World Wide Web Conference, WWW 2016, April 11th – 15th, 2016, Montreal, Canada
• 27th ACM Conference on Hypertext and Social Media, Hypertext 2016, July 10th – 13th, 2016, Halifax, Canada
• 15th IEEE International Conference on Data Mining, ICDM 2015, November 14th – 17th, 2015, Atlantic City, NJ, USA
• 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2014, August 24th – 27th, 2014, New York City, USA

Teaching (Lehre)

Supervised Theses

• Alexander Kohout: A Hybrid Classification–Based User Recommender System for Online Social Networks.
• Björn Fries: Einplatinencomputer-basierte Infreastruktur für RFID-Technik: Performanzanalyse und Einsatztauglichkeit.
• Jean Pascal Bauer: Sentiment-Analyse auf sozialen Medien. Der Einfluss von Community Entdeckung und Subjektivitätsanalyse als Vorverarbeitung.
• Dominik J. Erdmann: Identifikation und Evaluierung von Alternativen zu bestehender Software am Beispiel des Projektmanagement-Systems FusionForge.

Winter Semester 2015/16

• Praktikum Knowledge Discovery (Moodle)

Summer Semester 2015

• Web Science (Moodle)
• Datenbanken (Databases) (Moodle)
• Einführung in das Schreiben wissenschaftlicher Texte (im Bereich Informatik)

Winter Semester 2014/15

• Knowledge Discovery (Moodle)

Summer Semester 2014

• Einführung in das Schreiben wissenschaftlicher Texte (im Bereich Informatik), Seminar (Moodle)

Winter Semester 2013/14

• Knowledge Discovery (Moodle)
• Praktikum Knowledge Discovery (Moodle)
• Data-Mining für die Analyse sozialer Netzwerke (Seminar)

Summer Semester 2013

• Datenbanken (Databases) (Moodle)

Winter Semester 2012/13

• Einführung in die Künstliche Intelligenz (Introduction to Artificial Intelligence) (Moodle)

Events

2016

• Talk at LWDA 2016

2015

• Visiting PhD School on Complexity Science, Patras
• Conferator and short talk at SICSS Doctoral Retreat 2015
• Conferator and short talk at UIS 2015
• Talk at Doctoral Consortium ACM WSDM 2015, Shanghai, 02.02.2015
• Visiting Winter School on Web Search and Data Mining 2015, Shanghai

2014

• Visiting International Summer School 2014 Social Network Analysis, St.Petersburg
• Science Hack Day, re:publica (3sat report, Poster 1, Poster 2)
• EveryAware Project at CeBIT (c’t article, Post 1, Post 2)

2013

• Big Data Days, Berlin
• Talk at LWA 2013
• Conferator at INFORMATIK 2013
• Talk at Conference IEEE CPSCom 2013, WCC, Beijing, 22.08.2013
• Visiting Lipari Summer School 2013 Dynamic Networks and Social Behavior
• Talk at Workshop Modellierung von Vorgehensmodellen – Paradigmen, Sprachen, Tools, SE-2013, Aachen, 27.02.2013

2012

• Conferator at LWA 2012
• Conferator at VENUS review meeting (VENUS-Begehung)

Publications

2017

• Mining social media to inform peatland fire and haze disaster management. Kibanov, Mark; Stumme, Gerd; Amin, Imaduddin; Lee, Jong Gun (2017). 7(1) 30.

  Peatland fires and haze events are disasters with national, regional, and international implications. The phenomena lead to direct damage to local assets, as well as broader economic and environmental losses. Satellite imagery is still the main and often the only available source of information for disaster management. In this article, we test the potential of social media to assist disaster management. To this end, we compare insights from two datasets: fire hotspots detected via NASA satellite imagery and almost all GPS-stamped tweets from Sumatra Island, Indonesia, posted during 2014. Sumatra Island is chosen as it regularly experiences a significant number of haze events, which affect citizens in Indonesia as well as in nearby countries including Malaysia and Singapore. We analyze temporal correlations between the datasets and their geo-spatial interdependence. Furthermore, we show how Twitter data reveal changes in users' behavior during severe haze events. Overall, we demonstrate that social media are a valuable source of complementary and supplementary information for haze disaster management. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development.

2016

• DASHTrails: An Approach for Modeling and Analysis of Distribution-Adapted Sequential Hypotheses and Trails. Atzmueller, Martin; Schmidt, Andreas; Kibanov, Mark (2016).

2015

• Supporting Peat Fire Management using Social Media. Kibanov, Mark; Amin, Imaduddin; Lee, Jong Gun (2015).

  Peat fires and haze originating from such fires cause a large spectrum of ecological, social and economical problems as well as health issues. Indonesia is a country where peat fires are prevalent and the population suffers from the ensuing haze problems. Two Indonesian islands (Sumatra and Kalimantan) are most affected by peat fires. In this abstract, considering the fact that the usage of social media in Indonesia is high (with 72 million accounts in social networks), it is expected that insights generated from social media can help central and local authorities to improve peat fire management. In particular, we focus on peat fires in the year 2014 in Riau Province, which is one of the most haze-affected areas on Sumatra Island.
• Mining Groups Stability in Ubiquitous and Social Environments: Communities, Classes and Clusters. Kibanov, Mark in WSDM '15, X. Cheng, Li, H., Gabrilovich, E., Tang, J. (eds.) (2015). 441--446.

  Ubiquitous Computing is an emerging research area of computer science. Similarly, social network analysis and mining became very important in the last years. We aim to combine these two research areas to explore the nature of processes happening around users. The presented research focuses on exploring and analyzing different groups of persons or entities (communities, clusters and classes), their stability and semantics. An example of ubiquitous social data are social networks captured during scientific conferences using face-to-face RFID proximity tags. Another example of ubiquitous data is crowd-generated environmental sensor data. In this paper we generalize various problems connected to these and further datasets and consider them as a task for measuring group stability. Group stability can be used to improve state-of-the-art methods to analyze data. We also aim to improve the performance of different data mining algorithms, eg. by better handling of data with a skewed density distribution. We describe significant results some experiments that show how the presented approach can be applied and discuss the planned experiments.
• Adaptive Class Association Rule Mining for Human Activity Recognition. Atzmueller, Martin; Kibanov, Mark; Hayat, Naveed; Trojahn, Matthias; Kroll, Dennis M. Atzmueller, Lemmerich, F. (eds.) (2015).

  The analysis of human activity data is an important research area in the context of ubiquitous and social environments. Using sensor data obtained by mobile devices, e.g., utilizing accelerometer sensors contained in mobile phones, behavioral patterns and models can then be obtained. However, often the utilized models are often not simple to interpret by humans in order to facilitate assessment, evaluation and validation, e. g., in medical contexts. In this paper, we investigate human activity recognition using class association rule mining. We propose a novel approach for generating interpretable rule sets for classification: We present an adaptive framework for mining class association rules using subgroup discovery, and analyze different techniques for obtaining the final classifier. For our evaluation, we apply real-world data collected for different activities using mobile phone sensors.
• Is Web Content a Good Proxy for Real-Life Interaction? A Case Study Considering Online and Offline Interactions of Computer Scientists. Kibanov, Mark; Atzmueller, Martin; Illig, Jens; Scholz, Christoph; Barrat, Alain; Cattuto, Ciro; Stumme, Gerd (2015).

  Today, many people spend a lot of time online. Their social interactions captured in online social networks are an important part of the overall personal social profile, in addition to interactions taking place offline. This paper investigates whether relations captured by online social networks can be used as a proxy for the relations in offline social networks, such as networks of human face-to-face (F2F) proximity and coauthorship networks. Particularly, the paper focuses on interactions of computer scientists in online settings (homepages, social networks profiles and connections) and offline settings (scientific collaboration, face-to-face communications during the conferences). We focus on quantitative studies and investigate the structural similarities and correlations of the induced networks; in addition, we analyze implications between networks. Finally, we provide a qualitative user analysis to find characteristics of good and bad proxies.

2014

• Ubicon and its Applications for Ubiquitous Social Computing. Atzmueller, Martin; Becker, Martin; Kibanov, Mark; Scholz, Christoph; Doerfel, Stephan; Hotho, Andreas; Macek, Bjoern-Elmar; Mitzlaff, Folke; Mueller, Juergen; Stumme, Gerd (J. Bourgeois; Chin, A.; Yang, L. T., eds.) (2014). 20(1)

  The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the UBICON platform, its applications, and a large spectrum of analysis results. UBICON provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of UBICON. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing UBICON.
• Temporal Evolution of Contacts and Communities in Networks of Face-to-Face Human Interactions. Kibanov, Mark; Atzmueller, Martin; Scholz, Christoph; Stumme, Gerd (2014). 57(3)

  Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes, important influence factors, their effects, and their structural implications. In this article, we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. On a structural level, we focus on static and dynamic properties of the contact graphs. Also, we analyze the resulting community structure using state-of-the-art automatic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. Furthermore, we assess different factors which have an influence on the quality of com- munity prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.
• Predictability of Evolving Contacts and Triadic Closure in Human Face-to-Face Proximity Networks. Scholz, Christoph; Atzmueller, Martin; Kibanov, Mark; Stumme, Gerd (2014). 4(1)

  The analysis of link structures and particularly their dynamics is important for enhancing our understanding of the underlying (social) processes. This paper analyzes such structures in networks of face-to-face spatial proximity: we focus on evolving contacts and triadic closure and present new insights on the dynamic and static contact behavior in real-world networks, where we utilize face-to-face contact networks collected at three different conferences using the social conference guidance system Conferator [Atzmueller et al. 2011, 2014]. We analyze network dynamics and the predictability of all, new and recurring links. Furthermore, we especially investigate the strength of ties, their connection to triadic closure, and examine influence factors for predicting triadic closure in face-to-face proximity networks.
• Connect-U: A System for Enhancing Social Networking. Atzmueller, Martin; Behrenbruch, Kay; Hoffmann, Axel; Kibanov, Mark; Macek, Bjoern-Elmar; Scholz, Christoph; Skistims, Hendrik; Söllner, Matthias; Stumme, Gerd K. David, Geihs, K., Leimeister, J. M., Roßnagel, A., Schmidt, L., Stumme, G., Wacker, A. (eds.) (2014). 261-275.

  The application of ubiquitous and social computational systems shows a rapidly increasing trend in our everyday environments: Enhancing social interactions and communication in both online and real-world settings is an important issue in a broad range of application contexts. This chapter describes the development of ubiquitous and social software for enhancing social networking. The Connect-U demonstrator features a class of such applications. In particular, it comprises the Conferator and MyGroup applications for enabling smarter social interactions in the context of conferences and working groups. We describe the applied socio-technical design process, and discuss experiences and lessons learned.
• Die VENUS-Entwicklungsmethode Eine interdisziplinäre Methode für soziotechnische Softwaregestaltung Atzmüller, Martin; Baraki, Harun; Behrenbruch, Kay; Comes, Diana; Evers, Christoph; Hoffmann, Axel; Hoffmann, Holger; Jandt, Silke; Kibanov, Mark; Kieselmann, Olga; Kniewel, Romy; König, Immanuel; Macek, Björn‐Elmar; Niemczyk, Stefan; Scholz, Christoph; Schuldt, Michaela; Schulz, Thomas; Skistims, Hendrik; Söllner, Matthias; Voigtmann, Christian; Witsch, Andreas; Zirfas, Julia (A. Hoffmann; Niemczyk, S., eds.) (2014). (Vol. 1)

  Das multi-disziplinär besetzte VENUS-Forscherteam mit Experten aus den Bereichen Informatik, Mensch-Maschine-Schnittstelle, Vertrauensmanagement und Recht hat in einem iterativen Entwicklungsprozess eine systematische interdisziplinäre Entwicklungsmethode für die Gestaltung von ubiquitären Systemen erarbeitet. Der vorliegende Technische Bericht beschreibt die dabei entstandene VENUS-Entwicklungsmethode über den kompletten Entwicklungszyklus von der Bedarfsanalyse bis hin zur Systemevaluation. Die einzelnen Phasen der Softwareentwicklung werden durch integrierte Methoden und Techniken zur iterativen interdisziplinären Entwicklung sozialverträglicher ubiquitärer Systeme unterstützt. Es herrscht mittlerweile weitgehende Einigkeit darüber, dass solcher Art soziotechnische Systementwicklung zu Systemen führt, die von den Endnutzern mehr akzeptiert werden und einen größeren Mehrwert für alle Beteiligten bieten. Die hier vorgeschlagenen methodischen Bausteine sind für die Umsetzung eines soziotechnischen Ansatzes in der Praxis als Erweiterung existierender Softwareentwicklungsmethoden gedacht.
• Subjective vs. Objective Data: Bridging the Gap. Becker, Martin; Hotho, Andreas; Mueller, Juergen; Kibanov, Mark; Atzmueller, Martin; Stumme, Gerd (2014).

  Sensor data is objective. But when measuring our environment, measured values are contrasted with our perception, which is always subjective. This makes interpreting sensor measurements difficult for a single person in her personal environment. In this context, the EveryAware projects directly connects the concepts of objective sensor data with subjective impressions and perceptions by providing a collective sensing platform with several client applications allowing to explicitly associate those two data types. The goal is to provide the user with personalized feedback, a characterization of the global as well as her personal environment, and enable her to position her perceptions in this global context. In this poster we summarize the collected data of two EveryAware applications, namely WideNoise for noise measurements and AirProbe for participatory air quality sensing. Basic insights are presented including user activity, learning processes and sensor data to perception correlations. These results provide an outlook on how this data can further be used to understand the connection between sensor data and perceptions.

2013

• Towards the Ambient Classroom: An Environment for Enhancing Collaborative Educational Processes. Atzmueller, Martin; Bobek, Szymon; Kibanov, Mark; Nalepa, Grzegorz J. T. Roth-Berghofer, Oussena, S., Atzmueller, M. (eds.) (2013).

  With the rapid development of mobile technologies like, e.g., RFID tags, smartphones, and tablets, ambient intelligence applications have gained a huge popularity in recent years. However, most of the existing approaches aim at developing ambient environments that are rather static, and do not take the aspect of social interaction between the inhabitants into account. We argue that this is essential for smart classrooms, meeting rooms and other environments that are strictly based on mechanisms of human face-to-face interactions. In the context of the smart university, we propose the ambient classroom system for enhancing collaborative educational processes using sensor fusion, data mining, semantic technologies, and inference methods.
• Conferator - a Social System for Conference and Contact Management. Atzmueller, Martin; Kibanov, Mark; Scholz, Christoph; Stumme, Gerd (2013).
• On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity. Kibanov, Mark; Atzmueller, Martin; Scholz, Christoph; Stumme, Gerd J. E. Guerrero (ed.) (2013). 993--1000.

  Communities are a central aspect in the formation of social interaction networks. In this paper, we analyze the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific conferences. We compare the basic properties of the contact graphs to describe the properties of the contact networks and analyze the resulting community structure using state-of-the-art automic community detection algorithms. Specifically, we analyze the evolution of contacts and communities over time to consider the stability of the respective communities. In addition, we assess different factors which have an influence on the quality of community prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.
• How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks. Scholz, Christoph; Atzmueller, Martin; Kibanov, Mark; Stumme, Gerd J. G. Rokne, Faloutsos, C. (eds.) (2013). 356--363.

  Understanding the process of link creation is rather important for link prediction in social networks. Therefore, this paper analyzes contact structures in networks of face-to-face spatial proximity, and presents new insights on the dynamic and static contact behavior in such real world networks. We focus on face-to-face contact networks collected at different conferences using the social conference guidance system Conferator. Specifically, we investigate the strength of ties and its connection to triadic closures in face-to-face proximity networks. Furthermore, we analyze the predictability of all, new and recurring links at different points of time during the conference. In addition, we consider network dynamics for the prediction of new links.
• How to Select a Suitable Tool for a Software Development Project: Three Case Studies and the Lessons Learned. Kibanov, Mark; Erdmann, Dominik J.; Atzmueller, Martin S. Wagner, Lichter, H. (eds.) (2013).

  This paper describes a framework for evaluating and selecting suitable soft- ware tools for a software project, which is easily extendable depending on needs of the project. For an evaluation, we applied the presented framework in three different projects. These projects use different software development methods (from classical models to Scrum) in different environments (industry and academia). We discuss our experiences and the lessons learned.

2012

• Untersuchung von Versionsverwaltungssystemen mit Zielsetzung der Optimierung der kollaborativen Entwicklung. Technical Report (Master thesis), Kibanov, Mark PhD thesis, Humboldt-University of Berlin. (2012).

  Many new version control systems were developed in the last years. These compete with established systems as they implement some new concepts. These concepts influence the collaborative software development and even redefine it. Before a new system is introduced, it must be selected by product and process requirements. This thesis describes the evaluation of version control systems and the integration of the selected system by the example of one project of Capgemini Germany. Different properties of version control systems were examined and software development processes were analysed. The 3-staged process was applied for the selection of the control system version. This thesis also treats the problems of the integration of the selected system Git into the existing software development processes and project environment.
• Ubicon: Observing Social and Physical Activities. Atzmueller, Martin; Becker, Martin; Doerfel, Stephan; Kibanov, Mark; Hotho, Andreas; Macek, Björn-Elmar; Mitzlaff, Folke; Mueller, Juergen; Scholz, Christoph; Stumme, Gerd (2012). 317-324.

  The connection of ubiquitous and social computing is an emerging research area which is combining two prominent areas of computer science. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. Furthermore, we give an overview on the Ubicon platform which provides a framework for the creation and hosting of ubiquitous and social applications for diverse tasks and projects. Ubicon features the collection and analysis of both physical and social activities of users for enabling inter-connected applications in ubiquitous and social contexts. We summarize three real-world systems built on top of Ubicon, and exemplarily discuss the according mining and analysis aspects.