Christine Bauer

Christine Bauer
Utrecht University | UU · Department of Information and Computing Sciences

Dr.

About

157
Publications
123,812
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,434
Citations
Citations since 2017
69 Research Items
1060 Citations
2017201820192020202120222023050100150200
2017201820192020202120222023050100150200
2017201820192020202120222023050100150200
2017201820192020202120222023050100150200
Introduction
My research activities center on interactive intelligent systems where my research vision is to leverage intelligent systems and embed them into sociotechnical ecosystems to benefit humans and society. More details and a full list of publications can be found on https://christinebauer.eu
Additional affiliations
September 2020 - present
Utrecht University
Position
  • Professor (Assistant)
February 2020 - July 2020
Johannes Kepler University Linz
Position
  • PostDoc Position
March 2019 - February 2020
University of Innsbruck
Position
  • Lecturer
Description
  • course: Digital Markets VU course: Digital Markets SE course: Digital Society SE
Education
October 2006 - March 2011
TU Wien
Field of study
  • Business Informatics
October 2002 - July 2009
University of Vienna
Field of study
  • Social and Economic Sciences (Business Informatics)
September 1998 - June 2000
Konservatorium der Stadt Wien
Field of study
  • Jazz Saxophone

Publications

Publications (157)
Article
Full-text available
This paper’s main objective is to consolidate the knowledge on context in the realm of intelligent systems, systems that are aware of their context and can adapt their behavior accordingly. We provide an overview and analysis of 36 context models that are heterogeneous and scattered throughout multiple fields of research. In our analysis, we identi...
Article
Full-text available
Relevance: Popularity-based approaches are widely adopted in music recommendation systems, both in industry and research. These approaches recommend to the target user what is currently popular among all users of the system. However, as the popularity distribution of music items typically is a long-tail distribution, popularity-based approaches to...
Conference Paper
Full-text available
As recommender systems play an important role in everyday life, there is an increasing pressure that such systems are fair. Besides serving diverse groups of users, recommenders need to represent and serve item providers fairly as well. In interviews with music artists, we identified that gender fairness is one of the artists' main concerns. They e...
Article
Full-text available
The performance of recommender systems highly impacts both music streaming platform users and the artists providing music. As fairness is a fundamental value of human life, there is increasing pressure for these algorithmic decision-making processes to be fair as well. However, many factors make recommender systems prone to biases, resulting in unf...
Article
Full-text available
The diversity of the generated item suggestions can be an important quality factor of a recommender system. In offline experiments, diversity is commonly assessed with the help of the intra-list similarity (ILS) measure, which is defined as the average pairwise similarity of the items in a list. The similarity of each pair of items is often determi...
Conference Paper
Full-text available
Various social influences affect group decision-making processes. For instance, individuals may adapt their behavior to fit in with the group's majority opinion. Furthermore, ingroup favoritism may lead individuals to favor the ideas of ingroup members rather than the outgroup. So far, little is explored on how these phenomena of social conformity...
Article
Full-text available
Evaluation is a central step when it comes to developing, optimizing, and deploying rec-ommender systems. The PERSPECTIVES 2022 workshop at the 16th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current...
Conference Paper
Full-text available
Evaluation of recommender systems is a central activity when developing recommender systems, both in industry and academia. The second edition of the PERSPECTIVES workshop held at Rec-Sys 2022 brought together academia and industry to critically reflect on the evaluation of recommender systems. In the 2022 edition of PERSPECTIVES, we discussed prob...
Preprint
Full-text available
Our narrative literature review acknowledges that, although there is an increasing interest in recommender system fairness in general, the music domain has received relatively little attention in this regard. However, addressing fairness of music recommender systems (MRSs) is highly important because the performance of these systems considerably im...
Article
Full-text available
The comprehensive evaluation of the performance of a recommender system is a complex endeavor: many facets need to be considered in configuring an adequate and effective evaluation setting. Such facets include, for instance, defining the specific goals of the evaluation, choosing an evaluation method, underlying data, and suitable evaluation metric...
Conference Paper
Full-text available
In group decision-making, we can frequently observe that an individual adapts their behavior or belief to fit in with the group’s majority opinion. This phenomenon has been widely observed to exist especially against an objectively correct answer—in face-to-face and online interaction alike. To a lesser extent, studies have investigated the conform...
Chapter
Full-text available
Abstract: In this article, we explore explicit gendering in the manner in which voices are treated in music and audio and whether this relates to the specific function of the voice in a given context. Building on existing work on gender in singing, we explore the ways in which the voice is gendered through the use of voice production software. Spec...
Article
Full-text available
Music recommender systems have become an integral part of music streaming services such as Spotify and Last.fm to assist users navigating the extensive music collections offered by them. However, while music listeners interested in mainstream music are traditionally served well by music recommender systems, users interested in music beyond the main...
Article
Full-text available
Evaluation is a central step when it comes to developing, optimizing, and deploying recommender systems. The PERSPECTIVES 2021 workshop at the 15th ACM Conference on Recommender Systems brought together academia and industry to critically reflect on the evaluation of recommender systems. The primary goal of the workshop was to capture the current s...
Conference Paper
Full-text available
Evaluation is a cornerstone in the process of developing and deploying recommender systems. The PERSPECTIVES workshop brought together academia and industry to critically reflect on the evaluation of recommender systems. Particularly, the workshop aimed to shed light on the different, and maybe even diverging or contradictory perspectives on the ev...
Chapter
Music streaming platforms are currently among the main sources of music consumption, and the embedded recommender systems significantly influence what the users consume. There is an increasing interest to ensure that those platforms and systems are fair. Yet, we first need to understand what fairness means in such a context. Although artists are th...
Conference Paper
Full-text available
When evaluating personalized or adaptive systems, we frequently rely on one single evaluation objective and one single method. This remains us with “blind spots”. A comprehensive evaluation may require a thoughtful integration of multiple methods. This tutorial (i) demonstrates the wide variety of dimensions to be eval- uated, (ii) outlines the met...
Preprint
Full-text available
Music streaming platforms are currently among the main sources of music consumption, and the embedded recommender systems significantly influence what the users consume. There is an increasing interest to ensure that those platforms and systems are fair. Yet, we first need to understand what fairness means in such a context. Although artists are th...
Preprint
Full-text available
Music recommender systems have become an integral part of music streaming services such as Spotify and Last.fm to assist users navigating the extensive music collections offered by them. However, while music listeners interested in mainstream music are traditionally served well by music recommender systems, users interested in music beyond the main...
Article
Full-text available
Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what co...
Article
Recommender systems are among today’s most successful application areas of AI. However, in the recommender systems research community, we have fallen prey of a McNamara fallacy to a worrying extent: In the majority of our research efforts, we rely almost exclusively on computational measures such as prediction accuracy, which are easier to make tha...
Article
Full-text available
The 21st edition of the Annual Conference of the International Society for Music Information Retrieval (ISMIR) introduced so-called "special sessions," giving room for discussion on various topics related to music information retrieval (MIR). I report on the activities related to this special session No. 7 with the title "How do we---in MIR researc...
Conference Paper
Full-text available
Among the many viable research questions in the field of recom-mender systems, a frequently addressed problem is to accurately predict the relevance of individual items to users, with the goal of presenting the assumedly most relevant ones as recommendations. Typically, we have users' (explicit or implicit) ratings as input and rankings of items as...
Preprint
Full-text available
Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what co...
Conference Paper
Full-text available
A strong research record has evidenced that individuals tend to conform with a group's majority opinion. In contrast to existing literature that investigates conformity to a majority opinion against an objectively correct answer, the originality of our study lies in that we investigate conformity in a subjective context. The emphasis of our analysi...
Preprint
Full-text available
The analysis of consumers' personal information (PI) is a significant source to learn about consumers. In online settings, many consumers disclose PI abundantly -- this is particularly true for information provided on social network services. Still, people manage the privacy level they want to maintain by disclosing by disclosing PI accordingly. In...
Conference Paper
Full-text available
Research in the field of information retrieval and recommendation mostly focuses on one single evaluation method and one single quality objective. On the one hand, many research endeavors focus on system-centric evaluation from an algorithmic perspective and consider the context of use only to a minor extent. On the other hand, there are research e...
Preprint
Full-text available
In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. Our contribution is two-fold. First, we study the music genre preferences of this young user group and analyze these preferences for homogeneity within more fine-grained age groups and with respect to gender and cou...
Preprint
Full-text available
Popularity-based approaches are widely adopted in music recommendation systems, both in industry and research. However, as the popularity distribution of music items typically is a long-tail distribution, popularity-based approaches to music recommendation fall short in satisfying listeners that have specialized music. The contribution of this arti...
Preprint
Full-text available
In this paper, we focus on recommendation settings with multiple stakeholders with possibly varying goals and interests, and argue that a single evaluation method or measure is not able to evaluate all relevant aspects in such a complex setting. We reason that employing a multi-method evaluation, where multiple evaluation methods or measures are co...
Preprint
Full-text available
The task of a music recommender system is to predict what music item a particular user would like to listen to next. This position paper discusses the main challenges of the music preference prediction task: the lack of information on the many contextual factors influencing a user's music preferences in existing open datasets, the lack of clarity o...
Preprint
Full-text available
Socio-demographic user profiles are currently regarded as the most convenient base for successful personalized advertising. However, signs point to the dormant power of context recognition. While technologies that can sense the environment are increasingly advanced, questions such as what to sense and how to adapt to a consumer's context are largel...
Preprint
Full-text available
Promoting diversity in the music sector is widely discussed on the media. While the major problem may lie deep in our society, music information retrieval contributes to promoting diversity or may create unequal opportunities for artists. For example, considering the known problem of popularity bias in music recommendation, it is important to inves...
Conference Paper
Full-text available
Promoting diversity in the music sector is widely discussed on the media. While the major problem may lie deep in our society, music information retrieval contributes to promoting diversity or may create unequal opportunities for artists. For example, considering the known problem of popularity bias in music recommendation, it is important to inves...
Poster
Full-text available
We present a browsing interface that allows for an audiovisual exploration of regional music taste around the world. We exploit a total of 10,758,121 geolocated tweets about music. The web-based geo-aware visualization and auralization called Tastalyzer enables exploring and analyzing music taste on a fine-grained geographical level, such as (i) co...
Conference Paper
Full-text available
We present a browsing interface that allows for an audiovisual exploration of regional music taste around the world. We exploit a total of 10,758,121 geolocated tweets about music. The web-based geo-aware visualization and auralization called Tastalyzer enables exploring and analyzing music taste on a fine-grained geographical level, such as (i) co...
Conference Paper
Full-text available
In this paper, we focus on recommendation settings with multiple stakeholders with possibly varying goals and interests, and argue that a single evaluation method or measure is not able to evaluate all relevant aspects in such a complex setting. We reason that employing a multi-method evaluation, where multiple evaluation methods or measures are co...
Poster
Full-text available
In this paper, we focus on recommendation settings with multiple stakeholders with possibly varying goals and interests, and argue that a single evaluation method or measure is not able to evalu- ate all relevant aspects in such a complex setting. We reason that employing a multi-method evaluation, where multiple evaluation methods or measures are...
Poster
Full-text available
Social connections and cultural aspects play important roles in shaping an individual's preferences. For instance, people tend to select friends with similar music preferences. Furthermore, preferences and friending are influenced by cultural aspects. Recommender systems may benefit from these phenomena by using knowledge about the nature of social...
Conference Paper
Full-text available
The task of a music recommender system is to predict what music item a particular user would like to listen to next. This position paper discusses the main challenges of the music preference prediction task: the lack of information on the many contextual factors influencing a user’s music preferences in existing open datasets, the lack of clarity o...
Conference Paper
Full-text available
Social connections and cultural aspects play important roles in shaping an individual's preferences. For instance, people tend to select friends with similar music preferences. Furthermore, preferences and friending are influenced by cultural aspects. Recommender systems may benefit from these phenomena by using knowledge about the nature of social...
Conference Paper
Full-text available
Given the global expansion, the borderless nature, and the social impact of social media, this paper provides an examination of users' connection patterns in online social networks, more specifically the users' crosscountry connection patterns. We study three highly different social media platforms, Facebook, Last.fm, and 500px, and approach two ma...
Article
Full-text available
The emergence and on-going development of digital signage (DS) systems result in a growing number of technological capabilities of such systems. While these technological capabilities have attracted considerable research attention in informatics, studies exploring their application and impact are scarce. Marketing, and especially retailing, represe...
Conference Paper
Full-text available
We investigate the complex relationship between the factors (i) preference for music mainstream, (ii) social ties in an online music platform, and (iii) demographics. We define (i) on a global and a country level, (ii) by several network centrality measures such as Jaccard index among users' connections, closeness centrality, and betweenness centra...
Article
The music mainstreaminess of a listener reflects how strong a person’s listening preferences correspond to those of the larger population. Considering that music mainstream may be defined from different perspectives, we show country-specific differences and study how taking into account music mainstreaminess influences the quality of music recommen...
Conference Paper
Full-text available
We approach the research question whether real-world events, such as sport events or product launches, influence music consumption behavior. To this end, we consider events of different categories from Google Trends and model listening events as time series using Last.fm data. Performing an auto-regressive integrated moving average analysis to deco...
Article
Full-text available
The music mainstreaminess of a listener reflects how strong a person’s listening preferences correspond to those of the larger population. Considering that music mainstream may be defined from different perspectives, we show country-specific differences and study how taking into account music mainstreaminess influences the quality of music recommen...
Conference Paper
Full-text available
In the field of music recommender systems, country-specific aspects have received little attention, although it is known that music perception and preferences are shaped by culture; and culture varies across countries. Based on the LFM-1b dataset (including 53,258 users from 47 countries), we show that there are significant country-specific differe...
Conference Paper
Full-text available
The analysis of consumers' personal information (PI) is a significant source to learn about consumers. In online settings, many consumers disclose PI abundantly-this is particularly true for information provided on social network services. Still, people manage the privacy level they want to maintain by disclosing by disclosing PI accordingly. In ad...
Chapter
Dieser Artikel widmet sich der Perspektive der Informatik in der Musikwirtschaftsforschung. Zunächst wird der Erkenntnisgegenstand der Musikwirtschaftsforschung aus dieser Perspektive dargelegt und das zur Verfügung stehende Methodeninstrumentarium aufgezeigt. Dabei untermauert diese Arbeit, dass die Perspektive der Informatik in der Musikwirtschaf...
Conference Paper
Full-text available
The music mainstreaminess of a user reflects how strong a user's listening preferences correspond to those of the larger population. Considering that music mainstream may be defined from different perspectives and on various levels, e.g., geographical (charts of a country), genre ("Indie charts"), or distribution channel (radio charts vs. download...
Conference Paper
Full-text available
At the heart of ubiquitous and pervasive computing is the integration of semantically rich contextual information into systems that intelligently adapt their behavior to the context. This paper presents an analysis of the contextual elements considered in the scientific discourse on pervasive computing. To support researchers with positioning their...
Article
Full-text available
Ubiquitous business processes are the new generation of processes that pervade the physical space and interact with their environments using a minimum of human involvement. Although they are now widely deployed in the industry, their deployment is still ad hoc. They are implemented after an arbitrary modeling phase or no modeling phase at all. The...
Conference Paper
Full-text available
Due to the high potential of digital media to support learning processes and outcomes, educational games have gained wide acceptance over the years. The combination of mobile devices with location-based technologies offers new options and possibilities for the development of educational games in consideration of learners' environment with the posit...
Poster
Full-text available
Due to the high potential of digital media to support learning processes and outcomes, educational games have gained wide acceptance over the years. The combination of mobile devices with location-based technologies offers new options and possibilities for the development of educational games in consideration of learners’ environment with the posit...
Data
In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. Our contribution is two-fold. First, we study the music genre pref- erences of this young user group and analyze these preferences for homogeneity within more fine-grained age groups and with respect to gender and c...
Conference Paper
Full-text available
In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. Our contribution is two-fold. First, we study the music genre preferences of this young user group and analyze these preferences for homogeneity within more fine-grained age groups and with respect to gender and cou...
Conference Paper
Full-text available
ere is a long tradition in recommender systems research to eval- uate systems using quantitative performance measures on xed datasets. As a reaction to this narrow accuracy-based focus in research, novel qualities beyond pure accuracy are emphasized in recent research; among them are surprise and opposition. is position paper considers that the per...
Conference Paper
Full-text available
A music listener's mainstreaminess indicates the extent to which her listening preferences correspond to those of the population at large. However, formal definitions to quantify the level of mainstreaminess of a listener are rare and those available define mainstreaminess based on fractions between some kind of individual and global listening pro...
Data
Music Recommender Systems (MRS) are important drivers in music industry and are widely adopted by music platforms. Other than most MRS research exploring MRS from a technical or from a consumers’ perspective, this work focuses on the impact, value generation, challenges and opportunities for those, who contribute the core value, i.e. the artists. W...
Conference Paper
Full-text available
Music Recommender Systems (MRS) are important drivers in music industry and are widely adopted by music platforms. Other than most MRS research exploring MRS from a technical or from a consumers’ perspective, this work focuses on the impact, value generation, challenges and opportunities for those, who contribute the core value, i.e. the artists. W...
Conference Paper
Full-text available
Web 2.0 and social media have triggered radical changes in the very fundament of music business. In times before the Internet era, the music business was characterized by a standardized process including the creation, selection, distribution, and consumption of music. The roles of the involved market players (e.g. composer, lyricist, performer, pro...
Conference Paper
Full-text available
Designing layouts that are perceived as pleasant by the viewer is no easy task: it requires a wide variety of skills, including a sense for aesthetics. When numerous documents with different content need to be created, one of the bottlenecks is to manually create appealing layouts for each document. Thus, automation for aesthetic layout creation is...
Article
Full-text available
PURPOSE Various types and implementations of crowdsourcing have emerged on the market; many of them are related to logistics. While we can identify plenty of crowd logistics applications using information technology capabilities and information sharing in practice, theories behind this phenomenon have received only limited attention. This paper acc...
Conference Paper
Full-text available
The effects of benefits and risk beliefs on OSD are moderated by cultural differences, unlike those of privacy concerns and trust beliefs. Uncertainty avoidance and indulgence reduce the positive effect of benefits on OSD, masculinity and power distance enhance it. The negative effect of risk beliefs is reduced by uncertainty avoidance and long-ter...
Chapter
Information and communication technologies (ICT) are enablers for cooperative and collective online shopping. This novel phenomenon is also known under the terms “group buying” and “collective buying” and can be found in business-to-business (B2B) contexts as well as in business-to-consumer (B2C) shopping transactions. We investigate recent develop...
Conference Paper
Full-text available
Human-Computer Interaction research is traditionally collaborative. However, the current authorship model – i.e., placing authors’ names in a particular order – makes the contributions of collaborators who are not the “first author” (or not mentioned) less visible which negatively affects career paths. Still, if smaller and larger contributions are...
Data
Full-text available
Human-Computer Interaction research is traditionally collaborative. However, the current authorship model – i.e., placing authors’ names in a particular order – makes the contributions of collaborators who are not the “first author” (or not mentioned) less visible which negatively affects career paths. Still, if smaller and larger contributions are...
Article
Full-text available
Ubiquitous sensing allows systems to exploit almost any kind of context, and enables the design of intelligent systems that are aware of their context and adapt their behavior accordingly. As such systems have a number of properties, which distinguish them from traditional systems, their design requires a new approach to requirements engineering an...
Article
Full-text available
Context: Business Process Model and Notation (BPMN) is the de facto standard for business process modeling. It was developed by the Object Management Group with support of the major organizations in the fields of software engineering and information systems. Despite its wide use, when it comes to representing ubiquitous business processes, this bus...
Chapter
Full-text available
The market for digital signage has been growing at an accelerated pace for years. The benefits of novel approaches — such as contextualization and interaction functionalities — were soon recognized for achieving better advertising effects. However, the major types of digital signage currently in use have different requirements on the entire digital...
Article
Full-text available
Location-based advertising (LBA) allows the delivery of advertising messages to consumers in places that are known for their particular high and positive advertising effect. While LBA is recognized for static roadside billboards and the Web, LBA can now be found on mobile devices. This mobile advertising adds valuable opportunities for companies: i...
Data
Location-based advertising (LBA) allows the delivery of advertising messages to consumers in places that are known for their particular high and positive advertising effect. While LBA is recognized for static roadside billboards and the Web, LBA can now be found on mobile devices. This mobile advertising adds valuable opportunities for companies: i...