Publications
Explore the publications from our RecSys laboratory.
141.
Neidhardt, Julia; Schuster, Rainer; Seyfang, Leonhard; Werthner, Hannes
Eliciting the users’ unknown preferences Proceedings Article
In: Proceedings of the 8th ACM Conference on Recommender systems – RecSys ’14, ACM, New York, NY, USA, 2014.
@inproceedings{ 20.500.12708_55147,
title = {Eliciting the users' unknown preferences},
author = {Julia Neidhardt and Rainer Schuster and Leonhard Seyfang and Hannes Werthner},
doi = {10.1145/2645710.2645767},
year = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the 8th ACM Conference on Recommender systems - RecSys '14},
publisher = {ACM},
address = {New York, NY, USA},
abstract = {Personalized recommendation strongly relies on an accurate model to capture user preferences; eliciting this information is, in general, a hard problem. In the field of tourism this initial profiling becomes even more challenging. It has been shown that particularly in the beginning of the travel decision making process, users themselves are often not conscious of their needs and are not able to express them. In this paper, the basics of a picture-based approach are introduced that aims at revealing implicitly given user preferences. Based on a set of travel related pictures selected by a user, an individual travel profile is deduced. This is accomplished by mapping those pictures onto seven basic factors that reflect different travel behavioral aspects. Also tourism products can be represented by this seven factor model. Thus, this model constitutes the basis of our recommendation algorithm. First tests show that this non-verbal way of interaction is experienced as exiting and inspiring.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Personalized recommendation strongly relies on an accurate model to capture user preferences; eliciting this information is, in general, a hard problem. In the field of tourism this initial profiling becomes even more challenging. It has been shown that particularly in the beginning of the travel decision making process, users themselves are often not conscious of their needs and are not able to express them. In this paper, the basics of a picture-based approach are introduced that aims at revealing implicitly given user preferences. Based on a set of travel related pictures selected by a user, an individual travel profile is deduced. This is accomplished by mapping those pictures onto seven basic factors that reflect different travel behavioral aspects. Also tourism products can be represented by this seven factor model. Thus, this model constitutes the basis of our recommendation algorithm. First tests show that this non-verbal way of interaction is experienced as exiting and inspiring.
142.
Neidhardt, Julia
Social Influence Analysis in Online Travel Communities Miscellaneous
2013.
@misc{ 20.500.12708_84842,
title = {Social Influence Analysis in Online Travel Communities},
author = {Julia Neidhardt},
doi = {10.1007/978-3-642-36309-2},
year = {2013},
date = {2013-01-01},
abstract = {We propose a framework that integrates network analysis techniques as well as methods for social influence analysis of both static and dynamic networks. In the context of Web-based travel communities, this framework could lead to deeper insights on how members of such a community are influenced by others. First, we discuss the important role of the Web and of social media in today's tourism landscape. To understand Web-related phenomena a theoretical framework is needed that is able to capture those dynamics. Based on the state-of-the-art, we then introduce our conceptual and methodological approach. Expected results are on the one hand concrete statements about online travel communities and on the other hand a classification of methods related to network and social influence analysis.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
We propose a framework that integrates network analysis techniques as well as methods for social influence analysis of both static and dynamic networks. In the context of Web-based travel communities, this framework could lead to deeper insights on how members of such a community are influenced by others. First, we discuss the important role of the Web and of social media in today’s tourism landscape. To understand Web-related phenomena a theoretical framework is needed that is able to capture those dynamics. Based on the state-of-the-art, we then introduce our conceptual and methodological approach. Expected results are on the one hand concrete statements about online travel communities and on the other hand a classification of methods related to network and social influence analysis.
143.
Pobiedina, Nataliia; Neidhardt, Julia; Moreno, Maria Carmen Calatrava; Werthner, Hannes
Ranking Factors of Team Success Proceedings Article
In: WWW 2013 Companion, pp. 1185–1193, Companion Publication of the IW3C2 WWW 2013 Conference, 2013, ISBN: 978-1-4503-2038-2.
@inproceedings{ 20.500.12708_54595,
title = {Ranking Factors of Team Success},
author = {Nataliia Pobiedina and Julia Neidhardt and Maria Carmen Calatrava Moreno and Hannes Werthner},
isbn = {978-1-4503-2038-2},
year = {2013},
date = {2013-01-01},
booktitle = {WWW 2013 Companion},
pages = {1185–1193},
publisher = {Companion Publication of the IW3C2 WWW 2013 Conference},
abstract = {As an increasing number of human activities are moving to the Web, more and more teams are predominantly virtual. Therefore, formation and success of virtual teams is an important issue in a wide range of fields. In this paper we model social behavior patterns of team work using data from virtual communities. In particular, we use data about the Web community of the multiplayer online game Dota~2 to study cooperation within teams. By applying statistical analysis we investigate how and to which extent different factors of the team in the game, such as role distribution, experience, number of friends and national diversity, have an influence on the team's success. In order to complete the picture we also rank the factors according to their influence. The results of our study imply that cooperation within the team is better than competition.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
As an increasing number of human activities are moving to the Web, more and more teams are predominantly virtual. Therefore, formation and success of virtual teams is an important issue in a wide range of fields. In this paper we model social behavior patterns of team work using data from virtual communities. In particular, we use data about the Web community of the multiplayer online game Dota~2 to study cooperation within teams. By applying statistical analysis we investigate how and to which extent different factors of the team in the game, such as role distribution, experience, number of friends and national diversity, have an influence on the team’s success. In order to complete the picture we also rank the factors according to their influence. The results of our study imply that cooperation within the team is better than competition.
144.
Pobiedina, Nataliia; Neidhardt, Julia; Moreno, Maria Carmen Calatrava; Grad-Gyenge, Laszlo; Werthner, Hannes
On Successful Team Formation: Statistical Analysis of a Multiplayer Online Game Proceedings Article
In: 2013 IEEE 15th Conference on Business Informatics, IEEE, 2013.
@inproceedings{ 20.500.12708_54639,
title = {On Successful Team Formation: Statistical Analysis of a Multiplayer Online Game},
author = {Nataliia Pobiedina and Julia Neidhardt and Maria Carmen Calatrava Moreno and Laszlo Grad-Gyenge and Hannes Werthner},
doi = {10.1109/cbi.2013.17},
year = {2013},
date = {2013-01-01},
booktitle = {2013 IEEE 15th Conference on Business Informatics},
publisher = {IEEE},
abstract = {Teamwork plays an important role in many areas of today´s society, such as business activities. Thus, the question of how to form an effective team is of increasing interest. In this
paper we use the team-oriented multiplayer online game Dota 2 to study cooperation within teams and the success of teams. Making use of game log data, we choose a statistical approach to identify factors that increase the chance of a team to win. The factors
that we analyze are related to the roles that players can take within the game, the experiences of the players and friendship ties within a team. Our results show that such data can be used
to infer social behavior patterns.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Teamwork plays an important role in many areas of today´s society, such as business activities. Thus, the question of how to form an effective team is of increasing interest. In this
paper we use the team-oriented multiplayer online game Dota 2 to study cooperation within teams and the success of teams. Making use of game log data, we choose a statistical approach to identify factors that increase the chance of a team to win. The factors
that we analyze are related to the roles that players can take within the game, the experiences of the players and friendship ties within a team. Our results show that such data can be used
to infer social behavior patterns.
paper we use the team-oriented multiplayer online game Dota 2 to study cooperation within teams and the success of teams. Making use of game log data, we choose a statistical approach to identify factors that increase the chance of a team to win. The factors
that we analyze are related to the roles that players can take within the game, the experiences of the players and friendship ties within a team. Our results show that such data can be used
to infer social behavior patterns.
145.
Neidhardt, Julia
Social Influence Analysis Networks and Teams Technical Report
2013.
@techreport{ 20.500.12708_38664,
title = {Social Influence Analysis Networks and Teams},
author = {Julia Neidhardt},
year = {2013},
date = {2013-01-01},
abstract = {This report summarizes the research conducted during my time as a visiting scholar at the SONIC lab at Northwestern University, i.e., from August 2013 until November 2013. The work was done in close cooperation with Yun Huang and Prof. Noshir Contractor from SONIC lab. The research stay was funded by the Austrian Marshall Plan Foundation.},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
This report summarizes the research conducted during my time as a visiting scholar at the SONIC lab at Northwestern University, i.e., from August 2013 until November 2013. The work was done in close cooperation with Yun Huang and Prof. Noshir Contractor from SONIC lab. The research stay was funded by the Austrian Marshall Plan Foundation.
146.
Fensel, Anna; Neidhardt, Julia; Pobiedina, Nataliia; Fensel, Dieter; Werthner, Hannes
Towards an Intelligent Framework to Understand and Feed the Web Proceedings Article
In: Abramowicz, Witold; Domingue, John; Węcel, Krzysztof (Ed.): Business Information Systems Workshops, pp. 255–266, Springer, Berlin, Heidelberg, 2012, ISBN: 9783642342271.
@inproceedings{ 20.500.12708_54208,
title = {Towards an Intelligent Framework to Understand and Feed the Web},
author = {Anna Fensel and Julia Neidhardt and Nataliia Pobiedina and Dieter Fensel and Hannes Werthner},
editor = {Witold Abramowicz and John Domingue and Krzysztof Węcel},
doi = {10.1007/978-3-642-34228-8_24},
isbn = {9783642342271},
year = {2012},
date = {2012-01-01},
booktitle = {Business Information Systems Workshops},
pages = {255–266},
publisher = {Springer},
address = {Berlin, Heidelberg},
abstract = {The Web is becoming a mirror of the "real" physical world. More and more aspects of our life move to the Web, thus also transforming this world. And the diversity of ways to communicate over the Internet has enormously grown. In this context communicating the right thing at the right time in the right way to the right person has become a remarkable challenge. In this conceptual paper we propose a framework to apply semantic technologies in combination with statistical and learning methods on Web and social media data to build a decision support framework. This framework should help professionals as well as normal users to optimize the spread of their information and the potential impact of this information on the Web.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
The Web is becoming a mirror of the “real” physical world. More and more aspects of our life move to the Web, thus also transforming this world. And the diversity of ways to communicate over the Internet has enormously grown. In this context communicating the right thing at the right time in the right way to the right person has become a remarkable challenge. In this conceptual paper we propose a framework to apply semantic technologies in combination with statistical and learning methods on Web and social media data to build a decision support framework. This framework should help professionals as well as normal users to optimize the spread of their information and the potential impact of this information on the Web.
147.
Piazzi, Roland; Baggio, Rodolfo; Neidhardt, Julia; Werthner, Hannes
Network Analysis of the Austrian eTourism Web Proceedings Article
In: Proceedings of ENTER Conference 2012, pp. 356–367, Springer Wien New York, 2012, ISBN: 978-3-7091-1141-3.
@inproceedings{ 20.500.12708_53860,
title = {Network Analysis of the Austrian eTourism Web},
author = {Roland Piazzi and Rodolfo Baggio and Julia Neidhardt and Hannes Werthner},
isbn = {978-3-7091-1141-3},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of ENTER Conference 2012},
pages = {356–367},
publisher = {Springer Wien New York},
abstract = {Network analysis methods have gained much attention in the last years and have provided a wealth of insights into the structural and dynamic properties of many systems. Here these methods are applied to the study of a destination´s tourism webspace. This exploratory analysis aims at showing how these techniques can be used and what outcomes can be obtained. After a short introduction to network analysis and a brief review of the literature, the network analysis of the Austrian eTourism Web is described in detail. The data collection methods are explained and the characteristic network parameters are calculated. Then the results are discussed and interpreted.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Network analysis methods have gained much attention in the last years and have provided a wealth of insights into the structural and dynamic properties of many systems. Here these methods are applied to the study of a destination´s tourism webspace. This exploratory analysis aims at showing how these techniques can be used and what outcomes can be obtained. After a short introduction to network analysis and a brief review of the literature, the network analysis of the Austrian eTourism Web is described in detail. The data collection methods are explained and the characteristic network parameters are calculated. Then the results are discussed and interpreted.
148.
Piazzi, Roland; Baggio, Rodolfo; Neidhardt, Julia; Werthner, Hannes
Destinations and the Web: a Network Analysis View Journal Article
In: Information Technology and Tourism, vol. 13, iss. 3, pp. 215–228, 2011, ISSN: 1098-3058.
@article{ 20.500.12708_162802,
title = {Destinations and the Web: a Network Analysis View},
author = {Roland Piazzi and Rodolfo Baggio and Julia Neidhardt and Hannes Werthner},
doi = {10.3727/109830512x13283928066913},
issn = {1098-3058},
year = {2011},
date = {2011-01-01},
journal = {Information Technology and Tourism},
volume = {13},
issue = {3},
pages = {215–228},
abstract = {Network analysis methods have gained much attention in the last years and have provided a wealth of insights into the structural and dynamic properties of many systems. Here we apply these methods to the study of tourism destinations' webspaces. This exploratory analysis aims at showing how these techniques can be used and what outcomes can be obtained. After a short introduction to network analysis and a brief review of the literature, two cases are presented, namely Austria as a whole country and a smaller destination within Italy: the island of Elba. For each case, data collection methods are described and the characteristic network parameters are calculated. The comparison between the two cases highlights both similarities and differences, which are described and interpreted. Finally, the limitations of this approach are discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Network analysis methods have gained much attention in the last years and have provided a wealth of insights into the structural and dynamic properties of many systems. Here we apply these methods to the study of tourism destinations’ webspaces. This exploratory analysis aims at showing how these techniques can be used and what outcomes can be obtained. After a short introduction to network analysis and a brief review of the literature, two cases are presented, namely Austria as a whole country and a smaller destination within Italy: the island of Elba. For each case, data collection methods are described and the characteristic network parameters are calculated. The comparison between the two cases highlights both similarities and differences, which are described and interpreted. Finally, the limitations of this approach are discussed.