Disentangling individual biases in jury voting: an empirical analysis of voting behavior in the Eurovision Song Contest

The Eurovision Song Contest is one of the worldwide biggest live media events and the world’s leading broadcast of an international music competition. The countries of the European Broadcasting Union participate by sending an artist (or a group of artists) to the contest and both expert juries and the television audience of all participating countries vote in a special ranking and points system to determine the eventual winner. A substantial list of cultural economics papers empirically analyzed the voting behavior of juries (consisting of music industry professionals) and audiences to identify voting biases because of cultural and political influences on the voting bodies. Due to limited data availability, this literature suffered from having to treat the national juries as a black box even though they are composed of individuals with different demographic characteristics (age, gender, etc.) and expert backgrounds (industry managers, musicians, composers, music journalists, etc.). Our analysis benefits from utilizing new data about each individual member of the jury including their role within the jury (e.g., the chairperson) as well as about their individual votes in the ESC. Therefore, for the first time, we can disentangle the voting behavior of the juries and track the voting behavior of individual jury members. Based upon a rich dataset including personal characteristics (gender, age, career/professional background, nationality, cultural heritage, etc.) of both jury members (voters) and performing artists in the contest (voting objects), we analyze whether the increasing similarity between voter (jury member) and voting object (contest performer) correlates with upward biases in terms of awarded points. In doing so, we employ the concept of Mahalanobis distance to measure similarity and employ modern econometric regression methods to derive our results. Inter alia, we identify conditions under which the similarity of jury members with contestants leads to a pro-bias in voting (across different countries). Interestingly, the professional background of jury members also significantly influences the individual voting bias, for instance, experts with classical music backgrounds display significantly less bias than presenters of radio or television programs or music journalists. Altogether, our analysis allows us to look beyond the hitherto dominating “country X is biased for/against country Y” conclusions and track voting biases on an individual level, based on personal characteristics

An Investigation into Factors Which Explain the Scores and Voting Patterns of the Eurovision Song Contest.

The Eurovision Song Contest (ESC) is an annual international television song competition. Participating countries send a group or individual artist to perform an original song at the competition. The winner is decided by all participating countries using a voting system that incorporates both a public televote and an expert jury vote. Countries are excluded from voting for their entry and the country with the highest score wins. A high scoring performance and the voting patterns of the ESC can be explained by a complex set of factors. These factors can be divided into three groups; performance factors, competition factors and external factors. Performance factors relate to the performance itself, such as the song and the music. Competition factors relate to the way the competition is run and organised, such as the type of voting method used and the order of appearance for the performers. External factors encompass the social, cultural and political factors that influence voting at the Eurovision. The research presented here focuses on among other factors, whether voting blocs, music factors derived from Echo Nest services and migration patterns can explain the points and voting patterns of the 2016 ESC. The data was stratified into three datasets based on the voting systems; combined vote, televote and jury vote. A multiple linear regression model was fitted to each dataset and the significance of the predictor variables in explaining the response variable Points were evaluated using T-tests. The results showed that both the voting blocs and migration patterns were significant in explaining the scores and voting patterns of the competition. With regards to the music factors, the most successful songs appeared to be more acoustic and less dance orientated

Evaluation and Credentialing in Digital Music Communities

An examination of the use of digital badges as a reward for both casual online music evaluators and professional musicians.Professional and amateur musicians alike use social media as a platform for showcasing and promoting their music. Social media evaluation practices—rating, ranking, voting, “liking,” and “friending” by ordinary users, peers, and critics—have become essential promotional tools for musicians. In this report, H. Cecilia Suhr examines one recent development in online music evaluation: the use of digital badges to aid in assessment and evaluation. Digital badges have emerged in recent years as a potential credentialing method in informal learning environments. Suhr explores online music communities' use of digital badges as a reward for both casual music evaluators and musicians.Suhr examines the intersection of evaluation and gamification in Spotify's “Hit or Not” game, in which players assess a song's hit potential and receive digital badges as rewards, and considers the implications of turning music evaluation into a game. She then explores in detail the development of peer and professional critics on Indaba Music, a cloud-based collaboration platform where musicians earn badges through participating in contests. Suhr considers the emerging challenges and shortcomings of contest-based virtual communities and the value of badges, as perceived by Indaba musicians. She investigates to what extent digital badges can effectively represent and credit musicians' accomplishments and merits; describes the challenges, benefits, and shortcomings of digital badges as an evaluation mechanism; and compares the use of digital badges in assessing creativity to their use in learning and credentialing institutions

Judging by the Rules? The emergence of evaluation practices

How does evaluation work differently, and how do evaluation practices emerge, in different contexts? Drawing on a mixed-methods study of evaluation in figure skating and classical music, I discuss the divergent evaluative cultures in these settings, especially in terms of how formal and standardized they are, to consider how and why evaluation practices change over time and why different settings use different evaluation practices. I emphasize the importance of organizational structure, including context, competition structure, degree of centralization, and governance structure. My findings suggest that highly centralized settings governed by more powerful organizations and where competitions build on each other tend to use more formal and standardized evaluation practices compared to other settings with fewer constraints. Understanding how evaluation practices develop and what they look like in different contexts is important because in addition to influencing the objects of evaluation and perceived fairness and legitimacy, these practices often affect outcomes, which have significant consequences for participants

Pick Me! Pick Me!: Using Aristotelian Rhetorical Persuasion and Advertising Appeals for Self-Promotion

This project combines contemporary and classical rhetorical persuasion and applies them to self-promotion. Aristotle’s triad of modes of persuasion, ethos, pathos, and logos, represents classical persuasion. Appeals from advertising, such as humor, fear, music, and argumentum ad populum, represent the contemporary, but also are modern extensions of Aristotle’s triad. These concepts are then applied in such a way that the reader can see how they could use them to their benefit in influencing others. Each concept is defined and shown how it can be used in a spoken communicative way rather than a visual representation. Advertising appeals are typically put into place in commercials to visually show off the positive attributes of a product. For this project’s purpose, the reader is the product being shown off and both the Aristotelian modes and advertising appeals showcase how the reader can advertise himself or herself. To create a better understanding of the concepts outlined, they are then applied to three winners of the elimination-style competition reality show Survivor. On this show, contestants must vote out their fellow cast members, but subsequently stay in their good graces because the eliminated contestants get to decide the winner. Richard Hatch, Sandra Diaz-Twine, and Sarah Lacina all used the outlined concepts and create a verifiable example of how the concepts can be successfully used for the reader’s benefit

School of K-pop: Teaching a Nation Through Idol Survival Programs

Entering its third decade, hallyu—or the sudden global spread of Korean culture—has drawn renewed attention to Korean identity. K-pop idols continue to act as the main agents of hallyu. Since 2016, many of these idols began to debut through reality TV competition shows. Often referred to as “idol survival programs,” these shows are noteworthy for their large size, sudden popularity, and audience involvement. I use one such show, Produce 101, to argue that K-pop reality TV is a transnational space in which participants learn to configure their sense of place in the globalized modern world.Master of Art

Analysis of musical art trends in Ukraine in the 21st century

Thus, the development of Ukrainian music underwent a gradual evolution until the Russian aggression began in 2022. After the fall of the Soviet Union, Ukrainian-language music was not in favor, but after 2014 and especially after February 24, 2022, it became mainstream. Among Chusach varieties of musical art in Ukraine, the most common are pop, rock, rap, jazz, etc. The new opportunities that the Network has opened up for performers also have many hidden dangers. This is primarily about piracy, which significantly reduces the profits from selling your own. At the same time, thanks to multimedia and high-speed Internet, the exchange of musical novelties became more efficient. In particular, for a long time, Ukrainian music was characterized by the same trends as in the West: song plots, rhythms, popular styles of music, etc. It should be noted that the demand for Ukrainian music increased after Russia's military aggression. The Russian product was banned. So, if similar trends unfold in the same way, Ukraine will continue to see the emergence of new talented collectives. It should be noted that pop and rock are promising directions of music development but rap also looks extremely promising

Generalized weighting for bagged ensembles

Ensemble learning is a popular classification method where many individual simple learners contribute to a final prediction. Constructing an ensemble of learners has been shown to consistently improve prediction accuracy over a single learner. The most common types of ensembles include: bootstrap aggregated (bagged), boosted, and stacked. Each are different, yet has the same foundation of combining multiple learners. In this dissertation, we focus our attention to bagged ensembles; namely we propose a generalization by way of model weighting. The new method is motivated by the potential instability of averaging predictions of trees that may be of highly variable quality. To alleviate this, we replace the usual arithmetic average with a Cesaro average for weighted trees in the random forest. We provide both a theoretical analysis that gives exact conditions under which we would expect this weighted ensemble approach to do well, and numerical analysis that shows the new approach is competitive to other bagged ensembles when training a classification model on numerous realistic data sets. Going a step further we generalize our weights such that we allow simultaneous control over bias and variance. In particular, we introduce a regularization term that controls the variance reduction for bagged ensembles. Therefore, a new tunable weighted bagged ensemble framework is proposed, resulting in a very flexible method for classification. Using this methodology, we explore the impact tunable weighting has on the votes of each learner in an ensemble. To aid in the applicability of this body of work, the author discusses an R package that allows users to implement our proposed weighting scheme to arbitrary bagged ensembles. The package provides tools for constructing tunable bagged ensembles in the form of weights and is titled wbensembleR