Machine Learning on Publication Data

Higher-Order DeepTrails: Unified Approach to *Trails. Koopmann, Tobias; Pfister, Jan; Markus, André; Carolus, Astrid; Wienrich, Carolin; Hotho, Andreas. In Lernen, Wissen, Daten, Analysen {(LWDA)} Conference Proceedings, Marburg, Germany, October 9-11, 2023, Vol. 3630 of {CEUR} Workshop Proceedings, M. Leyer, J. Wichmann (eds.), pp. 372–386. CEUR-WS.org, 2023.

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@inproceedings{DBLP:conf/lwa/Koopmann23,
  author = {Koopmann, Tobias and Pfister, Jan and Markus, André and Carolus, Astrid and Wienrich, Carolin and Hotho, Andreas},
  booktitle = {Lernen, Wissen, Daten, Analysen {(LWDA)} Conference Proceedings, Marburg, Germany, October 9-11, 2023},
  editor = {Leyer, Michael and Wichmann, Johannes},
  keywords = {author:pfister},
  pages = {372–386},
  publisher = {CEUR-WS.org},
  series = {{CEUR} Workshop Proceedings},
  title = {Higher-Order DeepTrails: Unified Approach to *Trails},
  volume = 3630,
  year = 2023
}

Where to Submit? Helping Researchers to Choose the Right Venue. Kobs, Konstantin; Koopmann, Tobias; Zehe, Albin; Fernes, David; Krop, Philipp; Hotho, Andreas. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings, pp. 878–883. Association for Computational Linguistics, Online, 2020.

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@inproceedings{kobs-etal-2020-submit,
  address = {Online},
  author = {Kobs, Konstantin and Koopmann, Tobias and Zehe, Albin and Fernes, David and Krop, Philipp and Hotho, Andreas},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings},
  keywords = {author:zehe},
  month = 11,
  pages = {878–883},
  publisher = {Association for Computational Linguistics},
  title = {Where to Submit? Helping Researchers to Choose the Right Venue},
  year = 2020
}

What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus. In ACM Transactions on the Web, 10(2), pp. 14:1–14:32. 2016.

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Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.

@article{doerfel2016users,
  abstract = {Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  journal = {ACM Transactions on the Web},
  keywords = {selected},
  number = 2,
  pages = {14:1–14:32},
  title = {What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy},
  volume = 10,
  year = 2016
}

On Publication Usage in a Social Bookmarking System. Zoller, Daniel; Doerfel, Stephan; Jäschke, Robert; Stumme, Gerd; Hotho, Andreas. In Proceedings of the 2015 ACM Conference on Web Science. 2015.

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Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.

@inproceedings{zoller2015publication,
  abstract = {Scholarly success is traditionally measured in terms of citations to publications. With the advent of publication man- agement and digital libraries on the web, scholarly usage data has become a target of investigation and new impact metrics computed on such usage data have been proposed – so called altmetrics. In scholarly social bookmarking sys- tems, scientists collect and manage publication meta data and thus reveal their interest in these publications. In this work, we investigate connections between usage metrics and citations, and find posts, exports, and page views of publications to be correlated to citations.},
  author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas},
  booktitle = {Proceedings of the 2015 ACM Conference on Web Science},
  keywords = {bookmarking},
  title = {On Publication Usage in a Social Bookmarking System},
  year = 2015
}

How Social is Social Tagging?. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus. In Proceedings of the 23rd International World Wide Web Conference, of WWW 2014. ACM, New York, NY, USA, 2014.

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@inproceedings{doerfel2014social,
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  booktitle = {Proceedings of the 23rd International World Wide Web Conference},
  keywords = {behavior},
  publisher = {ACM},
  series = {WWW 2014},
  title = {How Social is Social Tagging?},
  year = 2014
}

Of course we share! Testing Assumptions about Social Tagging Systems. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus. 2014.

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Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.

@misc{doerfel2014course,
  abstract = {Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  keywords = {from:hotho},
  note = {cite arxiv:1401.0629},
  title = {Of course we share! Testing Assumptions about Social Tagging Systems},
  year = 2014
}

How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems. Niebler, Thomas; Singer, Philipp; Benz, Dominik; Körner, Christian; Strohmaier, Markus; Hotho, Andreas. In Advances in Information Retrieval, Vol. 7814, P. Serdyukov, P. Braslavski, S. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, E. Yilmaz (eds.), pp. 86–97. Springer Berlin Heidelberg, 2013.

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The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which

@incollection{niebler2013tagging,
  abstract = {The presence of emergent semantics in social annotation systems has been reported in numerous studies. Two important problems in this context are the induction of semantic relations among tags and the discovery of different senses of a given tag. While a number of approaches for discovering tag senses exist, little is known about which},
  author = {Niebler, Thomas and Singer, Philipp and Benz, Dominik and Körner, Christian and Strohmaier, Markus and Hotho, Andreas},
  booktitle = {Advances in Information Retrieval},
  editor = {Serdyukov, Pavel and Braslavski, Pavel and Kuznetsov, SergeiO. and Kamps, Jaap and Rüger, Stefan and Agichtein, Eugene and Segalovich, Ilya and Yilmaz, Emine},
  keywords = {from:hotho},
  pages = {86-97},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems},
  volume = 7814,
  year = 2013
}

Machine Learning on Publication Data

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