@article{mitzlaff2014social,
  abstract = {Applications of the Social Web are ubiquitous and have become an integral part of everyday life: Users make friends, for example, with the help of online social networks, share thoughts via Twitter, or collaboratively write articles in Wikipedia. All such interactions leave digital traces; thus, users participate in the creation of heterogeneous, distributed, collaborative data collections. In linguistics, the },
  author = {Mitzlaff, Folke and Atzmueller, Martin and Hotho, Andreas and Stumme, Gerd},
  doi = {10.1007/s13278-014-0216-2},
  eid = {216},
  interhash = {7e02f08a123c801c33ac93109394adfb},
  intrahash = {5b268a7c5308af783c3028573ffcd0c0},
  issn = {1869-5450},
  journal = {Social Network Analysis and Mining},
  language = {English},
  number = 1,
  publisher = {Springer Vienna},
  title = {The social distributional hypothesis: a pragmatic proxy for homophily in online social networks},
  url = {http://dx.doi.org/10.1007/s13278-014-0216-2},
  volume = 4,
  year = 2014
}

@article{10.1371/journal.pone.0081638,
  abstract = {<p>The development of ICT infrastructures has facilitated the emergence of new paradigms for looking at society and the environment over the last few years. Participatory environmental sensing, i.e. directly involving citizens in environmental monitoring, is one example, which is hoped to encourage learning and enhance awareness of environmental issues. In this paper, an analysis of the behaviour of individuals involved in noise sensing is presented. Citizens have been involved in noise measuring activities through the WideNoise smartphone application. This application has been designed to record both objective (noise samples) and subjective (opinions, feelings) data. The application has been open to be used freely by anyone and has been widely employed worldwide. In addition, several test cases have been organised in European countries. Based on the information submitted by users, an analysis of emerging awareness and learning is performed. The data show that changes in the way the environment is perceived after repeated usage of the application do appear. Specifically, users learn how to recognise different noise levels they are exposed to. Additionally, the subjective data collected indicate an increased user involvement in time and a categorisation effect between pleasant and less pleasant environments.</p>},
  author = {Becker, Martin and Caminiti, Saverio and Fiorella, Donato and Francis, Louise and Gravino, Pietro and Haklay, Mordechai (Muki) and Hotho, Andreas and Loreto, Vittorio and Mueller, Juergen and Ricchiuti, Ferdinando and Servedio, Vito D. P. and Sîrbu, Alina and Tria, Francesca},
  doi = {10.1371/journal.pone.0081638},
  interhash = {52652b4fe271d8be4b96b2f692fe9519},
  intrahash = {423a8aaa4eb317ee507143293205c76f},
  journal = {PLoS ONE},
  month = {12},
  number = 12,
  pages = {e81638},
  publisher = {Public Library of Science},
  title = {Awareness and Learning in Participatory Noise Sensing},
  url = {http://dx.doi.org/10.1371%2Fjournal.pone.0081638},
  volume = 8,
  year = 2013
}

@article{becker2013awareness,
  abstract = {The development of ICT infrastructures has facilitated the emergence
 of new paradigms for looking at society and the environment over
 the last few years. Participatory environmental sensing, i.e. directly
 involving citizens in environmental monitoring, is one example, which
 is hoped to encourage learning and enhance awareness of environmental
 issues. In this paper, an analysis of the behaviour of individuals
 involved in noise sensing is presented. Citizens have been involved
 in noise measuring activities through the WideNoise smartphone application.
 This application has been designed to record both objective (noise
 samples) and subjective (opinions, feelings) data. The application
 has been open to be used freely by anyone and has been widely employed
 worldwide. In addition, several test cases have been organised in
 European countries. Based on the information submitted by users,
 an analysis of emerging awareness and learning is performed. The
 data show that changes in the way the environment is perceived after
 repeated usage of the application do appear. Specifically, users
 learn how to recognise different noise levels they are exposed to.
 Additionally, the subjective data collected indicate an increased
 user involvement in time and a categorisation effect between pleasant
 and less pleasant environments.},
  author = {Becker, Martin and Caminiti, Saverio and Fiorella, Donato and Francis, Louise and Gravino, Pietro and Haklay, Mordechai (Muki) and Hotho, Andreas and Loreto, Vittorio and Mueller, Juergen and Ricchiuti, Ferdinando and Servedio, Vito D. P. and Sîrbu, Alina and Tria, Francesca},
  doi = {10.1371/journal.pone.0081638},
  interhash = {52652b4fe271d8be4b96b2f692fe9519},
  intrahash = {4b843a252dfa2c2616c18aea426f9861},
  issn = {1932-6203},
  journal = {PLOS ONE},
  month = dec,
  number = 12,
  pages = {e81638},
  title = {Awareness and Learning in Participatory Noise Sensing},
  volume = 8,
  year = 2013
}

@inproceedings{becker2013generic,
  abstract = {An increasing number of platforms like Xively or ThingSpeak are available to manage ubiquitous sensor data enabling the Internet of Things. Strict data formats allow interoperability and informative visualizations, supporting the development of custom user applications. Yet, these strict data formats as well as the common feed-centric approach limit the flexibility of these platforms. We aim at providing a concept that supports data ranging from text-based formats like JSON to images and video footage. Furthermore, we introduce the concept of extensions, which allows to enrich existing data points with additional information, thus, taking a data point centric approach. This enables us to gain semantic and user specific context by attaching subjective data to objective values. This paper provides an overview of our architecture including concept, implementation details and present applications. We distinguish our approach from several other systems and describe two sensing applications namely AirProbe and WideNoise that were implemented for our platform.},
  address = {New York, NY, USA},
  author = {Becker, Martin and Mueller, Juergen and Hotho, Andreas and Stumme, Gerd},
  booktitle = {1st International Workshop on Pervasive Urban Crowdsensing Architecture and Applications, PUCAA 2013, Zurich, Switzerland -- September 9, 2013. Proceedings},
  doi = {10.1145/2494091.2499776},
  interhash = {5302866e7849d40a44deab166b6c4d36},
  intrahash = {35eef1ecdac9d83d3bfbcac22c31984a},
  pages = {1175--1182},
  publisher = {ACM},
  title = {A Generic Platform for Ubiquitous and Subjective Data},
  year = 2013
}

@inproceedings{mueller2013recommendations,
  abstract = {With the rising popularity of smart mobile devices, sensor data-based
 applications have become more and more popular. Their users record
 data during their daily routine or specifically for certain events.
 The application WideNoise Plus allows users to record sound samples
 and to annotate them with perceptions and tags. The app is being
 used to document and map the soundscape all over the world. The procedure
 of recording, including the assignment of tags, has to be as easy-to-use
 as possible. We therefore discuss the application of tag recommender
 algorithms in this particular scenario. We show, that this task is
 fundamentally different from the well-known tag recommendation problem
 in folksonomies as users do no longer tag fix resources but rather
 sensory data and impressions. The scenario requires efficient recommender
 algorithms that are able to run on the mobile device, since Internet
 connectivity cannot be assumed to be available. Therefore, we evaluate
 the performance of several tag recommendation algorithms and discuss
 their applicability in the mobile sensing use-case.},
  author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings},
  interhash = {23d1cf49208d9a0c8b883dc69d4e444d},
  intrahash = {6190d6064dfdb3b8d71f2898539e993e},
  note = {accepted for publication},
  pages = {New York, NY, USA},
  publisher = {ACM},
  title = {Tag Recommendations for SensorFolkSonomies},
  year = 2013
}

@article{6069707,
  abstract = {An emerging category of devices at the edge of the Internet are consumer-centric mobile sensing and computing devices, such as smartphones, music players, and in-vehicle sensors. These devices will fuel the evolution of the Internet of Things as they feed sensor data to the Internet at a societal scale. In this article, we examine a category of applications that we term mobile crowdsensing, where individuals with sensing and computing devices collectively share data and extract information to measure and map phenomena of common interest. We present a brief overview of existing mobile crowdsensing applications, explain their unique characteristics, illustrate various research challenges, and discuss possible solutions. Finally, we argue the need for a unified architecture and envision the requirements it must satisfy.},
  author = {Ganti, R.K. and Ye, Fan and Lei, Hui},
  doi = {10.1109/MCOM.2011.6069707},
  interhash = {8e5a7301965e4703f5caaf45f7a823d4},
  intrahash = {44321e103e910e997453ffcb9877ac73},
  issn = {0163-6804},
  journal = {Communications Magazine, IEEE},
  number = 11,
  pages = {32-39},
  title = {Mobile crowdsensing: current state and future challenges},
  url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6069707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6069707},
  volume = 49,
  year = 2011
}

@inproceedings{mueller-2012,
  abstract = {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.},
  address = {Washington, DC, USA},
  author = {Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd},
  booktitle = {IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012},
  interhash = {a2695fd9fe6e76b252edbd42d72b34ad},
  intrahash = {90847b1d969ac1ed1f4c8d7146416619},
  publisher = {IEEE},
  title = {Ubicon: Observing Social and Physical Activities},
  year = 2012
}

@article{benz2010social,
  abstract = {Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.},
  address = {Berlin / Heidelberg},
  affiliation = {Knowledge &amp; Data Engineering Group, Research Center for Information Systems Design, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany},
  author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd},
  doi = {10.1007/s00778-010-0208-4},
  interhash = {57fe43734b18909a24bf5bf6608d2a09},
  intrahash = {c72ed831e0d752eb3613f90e45c71c44},
  issn = {1066-8888},
  journal = {The VLDB Journal},
  keyword = {Computer Science},
  number = 6,
  pages = {849-875},
  publisher = {Springer},
  title = {The social bookmark and publication management system bibsonomy},
  url = {http://dx.doi.org/10.1007/s00778-010-0208-4},
  volume = 19,
  year = 2010
}

@inproceedings{markines2009evaluating,
  abstract = {Social bookmarking systems and their emergent information structures, known as folksonomies, are increasingly important data sources for Semantic Web applications. A key question for harvesting semantics from these systems is how to extend and adapt traditional notions of similarity to folksonomies, and which measures are best suited for applications such as navigation support, semantic search, and ontology learning. Here we build an evaluation framework to compare various general folksonomy-based similarity measures derived from established information-theoretic, statistical, and practical measures. Our framework deals generally and symmetrically with users, tags, and resources. For evaluation purposes we focus on similarity among tags and resources, considering different ways to aggregate annotations across users. After comparing how tag similarity measures predict user-created tag relations, we provide an external grounding by user-validated semantic proxies based on WordNet and the Open Directory. We also investigate the issue of scalability. We ?nd that mutual information with distributional micro-aggregation across users yields the highest accuracy, but is not scalable; per-user projection with collaborative aggregation provides the best scalable approach via incremental computations. The results are consistent across resource and tag similarity.},
  author = {Markines, Benjamin and Cattuto, Ciro and Menczer, Filippo and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {18th International World Wide Web Conference},
  interhash = {a266558ad4d83d536a0be2ac94b6b7df},
  intrahash = {d16e752a8295d5dad7e26b199d9f614f},
  month = {April},
  pages = {641--650},
  title = {Evaluating Similarity Measures for Emergent Semantics of Social Tagging},
  url = {http://www2009.eprints.org/65/},
  year = 2009
}