Team
Julia Neidhardt
Researcher & Lab Director
Julia Neidhardt is a researcher at the Research Unit E-Commerce at TU Wien informatics with a background in mathematics and computer science. Previously she was a guest researcher at the Austrian Academy of Sciences as well as visiting scholar at Northwestern University, USA, and at the University of Geneva, Switzerland. Her research focuses on user modeling and recommender systems in tourism and in the news domain, developing approaches to capture online opinion-forming and online behavior, and digital humanities. Her research is published in highly renowned conference proceedings and journals including Nature Human Behaviour. She regularly is invited to give talks on topics related to her research, among others at the Oxford Women in Computer Science – Distinguished Speaker Series at the University of Oxford. Julia Neidhardt is a senior program committee member of the ACM Conference on Recommender Systems (RecSys) and is an associate editor of the Journal of Information Technology &Tourism as well as a distinguished reviewer of the newly established journal ACM Transactions on Recommender Systems (TORS). She was research track co-chair of ENTER 2020 and ENTER 2019 and a co-organizer of a number of workshops and conferences. Julia Neidhardt is part of the Digital Humanism Initiative at TU Wien and board member of Center for Artificial Intelligence and Machine Learning (CAIML). She will lead the CD Lab for Recommender Systems, applying her expertise in these various research areas focusing on recommender systems.
Publications
2015
Krathu, Worarat; Pichler, Christian; Xiao, Guohui; Werthner, Hannes; Neidhardt, Julia; Zapletal, Marco; Huemer, Christian
Inter-organizational success factors: a cause and effect model Journal Article
In: Information Systems and E-Business Management, vol. 13, iss. 3, pp. 553–593, 2015, ISSN: 1617-9846.
@article{ 20.500.12708_150395,
title = {Inter-organizational success factors: a cause and effect model},
author = {Worarat Krathu and Christian Pichler and Guohui Xiao and Hannes Werthner and Julia Neidhardt and Marco Zapletal and Christian Huemer},
doi = {10.1007/s10257-014-0258-z},
issn = {1617-9846},
year = {2015},
date = {2015-01-01},
journal = {Information Systems and E-Business Management},
volume = {13},
issue = {3},
pages = {553–593},
abstract = {Inter-organizational systems form the basis for successful business collaboration in the Internet and B2B e-commerce era. To properly design and manage such systems one needs to understand the structure and dynamics of the relationships between organizations. The evaluation of such inter-organizational relationships (IORs) is normally conducted using "success factors". These are often referred to as constructs, such as trust and information sharing. In strategic management and performance analysis, different methods are employed for evaluating business performance and strategies, such as the Balanced Scorecard (BSC) method. The BSC utilizes success factors for measuring and monitoring IORs against business strategies. For these reasons, a thorough understanding of success factors, the relationships between them, as well as their relationship to business strategies is required. In other words, understanding success factors allows strategists deriving measurements for success factors as well as aligning these success factors with business strategies. This underpins nowadays close relationship between business strategy, IORs and their realization by means of inter-organizational systems. In this paper, we present (1) a systematic literature review studying success factors and their impact on IORs as well as (2) an analysis of the results found. The review is based on 177 publications, published between 2000 and 2012, dealing with factors influencing IORs. The work presented provides an overview on success factors, influencing relationships between success factors, as well as their influence on the success of IORs. The work is somehow "meta-empirical" as it only looks at published studies and not on own cases. Consequently, it is based on the assumption that studies in scientific literature represent the real-world. The constructs and relationships found in the review are grouped based on their scope and summarized in a cause and effect model. The grouping of constructs results in five groups including Relationship Orientation, Relational Norm, Relational Capital, Atmosphere, and Others. Since the cause and effect model represents a directed graph, different network analysis methods may be applied for analyzing the model. In particular, an in- and out-degree analysis is applied on the cause and effect model for detecting the most influencing as well as the most influenced success factors.},
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pubstate = {published},
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Inter-organizational systems form the basis for successful business collaboration in the Internet and B2B e-commerce era. To properly design and manage such systems one needs to understand the structure and dynamics of the relationships between organizations. The evaluation of such inter-organizational relationships (IORs) is normally conducted using “success factors”. These are often referred to as constructs, such as trust and information sharing. In strategic management and performance analysis, different methods are employed for evaluating business performance and strategies, such as the Balanced Scorecard (BSC) method. The BSC utilizes success factors for measuring and monitoring IORs against business strategies. For these reasons, a thorough understanding of success factors, the relationships between them, as well as their relationship to business strategies is required. In other words, understanding success factors allows strategists deriving measurements for success factors as well as aligning these success factors with business strategies. This underpins nowadays close relationship between business strategy, IORs and their realization by means of inter-organizational systems. In this paper, we present (1) a systematic literature review studying success factors and their impact on IORs as well as (2) an analysis of the results found. The review is based on 177 publications, published between 2000 and 2012, dealing with factors influencing IORs. The work presented provides an overview on success factors, influencing relationships between success factors, as well as their influence on the success of IORs. The work is somehow “meta-empirical” as it only looks at published studies and not on own cases. Consequently, it is based on the assumption that studies in scientific literature represent the real-world. The constructs and relationships found in the review are grouped based on their scope and summarized in a cause and effect model. The grouping of constructs results in five groups including Relationship Orientation, Relational Norm, Relational Capital, Atmosphere, and Others. Since the cause and effect model represents a directed graph, different network analysis methods may be applied for analyzing the model. In particular, an in- and out-degree analysis is applied on the cause and effect model for detecting the most influencing as well as the most influenced success factors.
Neidhardt, Julia; Seyfang, Leonhard; Schuster, Rainer; Werthner, Hannes
A picture-based approach to recommender systems Journal Article
In: Information Technology and Tourism, vol. 15, iss. 1, pp. 49–69, 2015, ISSN: 1098-3058.
@article{ 20.500.12708_150411,
title = {A picture-based approach to recommender systems},
author = {Julia Neidhardt and Leonhard Seyfang and Rainer Schuster and Hannes Werthner},
doi = {10.1007/s40558-014-0017-5},
issn = {1098-3058},
year = {2015},
date = {2015-01-01},
journal = {Information Technology and Tourism},
volume = {15},
issue = {1},
pages = {49–69},
abstract = {Due to their complexity, tourism products present major challenges to recommender techniques. Especially the assessment of customer preferences in order to get accurate user profiles is a non-trivial task for several reasons: (a) tourism is an "emotional" experience, which is typically hard to capture by using rational terms; (b) particularly in early phases of a travel decision process, users are not able to explicitly express their preferences; (c) and they are often lacking domain knowledge and thus have difficulties to use the right terminology. In this paper we introduce an alternative, i.e., a picture-based approach, as a new method to implicitly elicit user preferences for tourism products. We develop a model in which a user's travel profile is composed of seven basic factors. The scores of these factors are determined by asking the user to select a number of pictures that are appealing to him or her. The model as well as its implementation into a recommender system are described in detail. First evaluations show that interactions with the system are perceived as inspiring and enjoyable.},
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Due to their complexity, tourism products present major challenges to recommender techniques. Especially the assessment of customer preferences in order to get accurate user profiles is a non-trivial task for several reasons: (a) tourism is an “emotional” experience, which is typically hard to capture by using rational terms; (b) particularly in early phases of a travel decision process, users are not able to explicitly express their preferences; (c) and they are often lacking domain knowledge and thus have difficulties to use the right terminology. In this paper we introduce an alternative, i.e., a picture-based approach, as a new method to implicitly elicit user preferences for tourism products. We develop a model in which a user’s travel profile is composed of seven basic factors. The scores of these factors are determined by asking the user to select a number of pictures that are appealing to him or her. The model as well as its implementation into a recommender system are described in detail. First evaluations show that interactions with the system are perceived as inspiring and enjoyable.
Werthner, Hannes; Alzua-Sorzabal, Aurkene; Cantoni, Lorenzo; Dickinger, Astrid; Gretzel, Ulrike; Jannach, Dietmar; Neidhardt, Julia; Pröll, Birgit; Ricci, Francesco; Scaglione, Miriam; Stangl, Brigitte; Stock, Oliviero; Zanker, Markus
Future research issues in IT and tourism Journal Article
In: Information Technology and Tourism, vol. 15, iss. 1, pp. 1–15, 2015, ISSN: 1098-3058.
@article{ 20.500.12708_150597,
title = {Future research issues in IT and tourism},
author = {Hannes Werthner and Aurkene Alzua-Sorzabal and Lorenzo Cantoni and Astrid Dickinger and Ulrike Gretzel and Dietmar Jannach and Julia Neidhardt and Birgit Pröll and Francesco Ricci and Miriam Scaglione and Brigitte Stangl and Oliviero Stock and Markus Zanker},
doi = {10.1007/s40558-014-0021-9},
issn = {1098-3058},
year = {2015},
date = {2015-01-01},
journal = {Information Technology and Tourism},
volume = {15},
issue = {1},
pages = {1–15},
abstract = {The objective of this manifesto (as a result of the JITT workshop in June 2014) is to identify a list of pivotal research topics and issues in e-tourism. E-tourism can be seen as everything that happens electronically in the travel and tourism industry/experience; more formally it is defined as the design, implementation and application of IT and ecommerce solutions in the travel and tourism industry as well as the analysis of the impact of the respective technical and economic processes and market structures on all the involved actors and especially on the traveller's experience. In tourism as an "information business", Information Technology has always played an important role since the 1960s with the computerized reservation systems/global distribution systems; these were one of the first world-wide electronic networks. And since the beginning of the Web in the early 1990s, travel and tourism was and is a major application domain for Web-based services. As such, the domain is also a major driver of technological innovation. This manifesto provides guidelines on strategic research issues for the research community, but as such it is also conceived as a basis document for industry and policy makers.},
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pubstate = {published},
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The objective of this manifesto (as a result of the JITT workshop in June 2014) is to identify a list of pivotal research topics and issues in e-tourism. E-tourism can be seen as everything that happens electronically in the travel and tourism industry/experience; more formally it is defined as the design, implementation and application of IT and ecommerce solutions in the travel and tourism industry as well as the analysis of the impact of the respective technical and economic processes and market structures on all the involved actors and especially on the traveller’s experience. In tourism as an “information business”, Information Technology has always played an important role since the 1960s with the computerized reservation systems/global distribution systems; these were one of the first world-wide electronic networks. And since the beginning of the Web in the early 1990s, travel and tourism was and is a major application domain for Web-based services. As such, the domain is also a major driver of technological innovation. This manifesto provides guidelines on strategic research issues for the research community, but as such it is also conceived as a basis document for industry and policy makers.
2014
Neidhardt, Julia; Huang, Yun; Contractor, Noshir
Assembly factors influencing the victor in head to head short duration team competitions in a multiplayer online battle arena game Miscellaneous
2014.
@misc{ 20.500.12708_86039,
title = {Assembly factors influencing the victor in head to head short duration team competitions in a multiplayer online battle arena game},
author = {Julia Neidhardt and Yun Huang and Noshir Contractor},
year = {2014},
date = {2014-01-01},
abstract = {While network approaches are used to study how the assembly of teams impacts their performance, there has been little attention to assess the impact of assembly on the relative performance of two teams in a head to head contest. In this study, we focus specifically on assembly factors that influence performance of short-duration contests in mid-sized teams playing a multiplayer online game, Dota2, where two teams consisting of five players each compete with each other. We determine the attributes and relational factors that help a team to defeat the opponent. Among attributes we consider the players' skills as well as the diversity of their skills and their roles. Relational factors include the friendship relations within a team, previous co-playing experiences of team members as well as the embeddedness of the team, i.e., whether team members belong to a community that often plays together. We use game log data for short matches (under 30 minutes) within Dota2 to empirically test this model. We find that teams with players who have more diverse roles are more likely to win. We also find some evidence that teams consisting of players who have focused on training their fighting skills rather than on non-fighting skills have an advantage. However, when relational factors are included in the model, some skill factors are no longer significant. Instead, friendship ties between team members as well as the embeddedness of the team within the community have a positive impact on the likelihood of a team to win.},
keywords = {},
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While network approaches are used to study how the assembly of teams impacts their performance, there has been little attention to assess the impact of assembly on the relative performance of two teams in a head to head contest. In this study, we focus specifically on assembly factors that influence performance of short-duration contests in mid-sized teams playing a multiplayer online game, Dota2, where two teams consisting of five players each compete with each other. We determine the attributes and relational factors that help a team to defeat the opponent. Among attributes we consider the players’ skills as well as the diversity of their skills and their roles. Relational factors include the friendship relations within a team, previous co-playing experiences of team members as well as the embeddedness of the team, i.e., whether team members belong to a community that often plays together. We use game log data for short matches (under 30 minutes) within Dota2 to empirically test this model. We find that teams with players who have more diverse roles are more likely to win. We also find some evidence that teams consisting of players who have focused on training their fighting skills rather than on non-fighting skills have an advantage. However, when relational factors are included in the model, some skill factors are no longer significant. Instead, friendship ties between team members as well as the embeddedness of the team within the community have a positive impact on the likelihood of a team to win.
Huang, Yun; Neidhardt, Julia; Contractor, Noshir
Why Players Leave: Exploring Major Factors of Quitting EverQuest II Miscellaneous
2014.
@misc{ 20.500.12708_86040,
title = {Why Players Leave: Exploring Major Factors of Quitting EverQuest II},
author = {Yun Huang and Julia Neidhardt and Noshir Contractor},
year = {2014},
date = {2014-01-01},
abstract = {In online games as well as many online social sites, the success and attractiveness of a community is strongly determined by the active participation of its members. Analyzing why people leave and predicting churn behavior becomes a critical challenge, especially with the mutual influence among users. The purpose of this paper is to explore important factors that influence quitting decisions in games from three dimensions: achievement, commitment, and social network effects. In EverQuest II, a massively multiplayer online role-playing game, we identify different player attributes such as their progress and rewards in game, time committed on different game activities, and team and organization relations and examine their impacts on the likelihood of unsubscribing the game. In particular, we focus on social influence in players' teaming network and characterize the contagious effect of quitting behavior. We use a generalization of Exponential Random Graph Models (ERGM/p*) to study the social influence among users who played together. Our results show that players with higher achievement, such as higher levels, more award items, and more kills, are less likely to quit the game. The commitment on game activities has a mixed effect: players spend more time on building items are more likely to quit but players spend more time on trading items are less likely to quit. For social effects, we find that players who have more teammates and join a guild are less likely to quit. However, the likelihood of quitting increases significantly with the number of quitting teammates.},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
In online games as well as many online social sites, the success and attractiveness of a community is strongly determined by the active participation of its members. Analyzing why people leave and predicting churn behavior becomes a critical challenge, especially with the mutual influence among users. The purpose of this paper is to explore important factors that influence quitting decisions in games from three dimensions: achievement, commitment, and social network effects. In EverQuest II, a massively multiplayer online role-playing game, we identify different player attributes such as their progress and rewards in game, time committed on different game activities, and team and organization relations and examine their impacts on the likelihood of unsubscribing the game. In particular, we focus on social influence in players’ teaming network and characterize the contagious effect of quitting behavior. We use a generalization of Exponential Random Graph Models (ERGM/p*) to study the social influence among users who played together. Our results show that players with higher achievement, such as higher levels, more award items, and more kills, are less likely to quit the game. The commitment on game activities has a mixed effect: players spend more time on building items are more likely to quit but players spend more time on trading items are less likely to quit. For social effects, we find that players who have more teammates and join a guild are less likely to quit. However, the likelihood of quitting increases significantly with the number of quitting teammates.
Neidhardt, Julia
A picture-based approach for travel recommendations Miscellaneous
2014.
@misc{ 20.500.12708_85978,
title = {A picture-based approach for travel recommendations},
author = {Julia Neidhardt},
year = {2014},
date = {2014-01-01},
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. Aiming at revealing implicitly given user preferences, this work introduces an approach that utilizes a set of travel related pictures to discover users' travel behavior and in turn, to deliver recommendations. Users first select three to seven pictures they like when thinking about their future travels. Then the selected pictures are mapped onto seven preference factors that reflect different travel behavioral aspects. The scores of the factors are used to recommend touristic point of interests. The pilot study shows that users are more motivated and satisfied using this non-verbal way of interaction. This talk discusses a stream of studies to quantify intangible user preferences and provide an easy and playful method to generate inputs/data for recommendation systems.},
keywords = {},
pubstate = {published},
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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. Aiming at revealing implicitly given user preferences, this work introduces an approach that utilizes a set of travel related pictures to discover users’ travel behavior and in turn, to deliver recommendations. Users first select three to seven pictures they like when thinking about their future travels. Then the selected pictures are mapped onto seven preference factors that reflect different travel behavioral aspects. The scores of the factors are used to recommend touristic point of interests. The pilot study shows that users are more motivated and satisfied using this non-verbal way of interaction. This talk discusses a stream of studies to quantify intangible user preferences and provide an easy and playful method to generate inputs/data for recommendation systems.
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.
2013
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}
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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.
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 = {},
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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.
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.
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},
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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.
2012
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},
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}
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.
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.
2011
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.