Show Your Face! Investigating the Relationship Between Human Faces and Music’s Success

Streaming services are becoming the primary source for media consumption. Particularly platforms like SoundCloud, where users can disseminate user-generated content (UGC), are gaining relevance. To shed light into the drivers which positively influence the number of listeners, we draw from marketing literature related to depictions of people, which suggests that human faces can contribute to a higher degree of brand liking or brand identification. Thereupon, we propose a hypothesis which suggests that human faces on cover arts likewise generate more plays. We follow a data science approach using 1754 observations from SoundCloud and apply Google’s facial recognition API (Vision AI) to examine the impact of human faces on music’s success. We provide initial evidence that tracks with a human-face cover art yield in a higher number of plays compared to tracks with a cover art without a human face

What are you looking at? Using eye tracking to improve learning in virtual environments

Learning in Virtual Reality (VR) is an emerging topic characterized by opposing theories. The interest theory hypothesizes that students who learned in immersive VR would report more positive ratings of interest and motivation and would thus score higher on a test covering the lesson learned. On the other hand, the cognitive theory of multimedia learning assumes that students who learned with a classic medium would score higher on a test covering the lesson learned, while reporting lower in terms of interest and motivation. In this proposal, I focus on the concept of learning in VR, which is an emerging concept in information science (IS) research that can be studied using neurological measures such as eye tracking. While previous literature has provided initial evidence of the feasibility of eye tracking in a learning context, this study seeks to investigate how well eye tracking performs when it comes to detecting items inducing superfluous cognitive load in a VR setting

How algorithms work and play together

Pricing decisions are increasingly made by algorithms. To assess if reinforcement learning algorithms are able to reach a state of collusion autonomously and thereby may breach the cartel prohibition under Article 101(1) TFEU, we have built a simplified algorithmic scenario based on a modified version of a prisoner’s dilemma where three agents play the game of rock-paper-scissors. First, we describe how the used reinforcement learning algorithms work. We then have a look at their conduct during a multitude of game rounds, concluding that eventually they all settle in an equilibrium of a specific reward rate. We observe that all three agents achieve this by developing and following specific action patterns. However, it is not clear whether the agents simply consider the likely response of the competing agents (tacit collusion) or rather knowingly substitute practical long-term cooperation for competition (concerted practice). Moreover, this observation cannot be tied to one specific move, sequence or situation symbolizing an initial concertation which then is followed by a respective subsequent conduct. One approach to account for this characteristic of algorithmic behavior could be to assume a simultaneity of concertation and conduct. Another possibility could be to omit a distinct identification of concertation and subsequent conduct and to make basic assumptions for one or the other

Winning at any cost - infringing the cartel prohibition with reinforcement learning

Pricing decisions are increasingly made by AI. Thanks to their ability to train with live market data while making decisions on the fly, deep reinforcement learning algorithms are especially effective in taking such pricing decisions. In e-commerce scenarios, multiple reinforcement learning agents can set prices based on their competitor's prices. Therefore, research states that agents might end up in a state of collusion in the long run. To further analyze this issue, we build a scenario that is based on a modified version of a prisoner's dilemma where three agents play the game of rock paper scissors. Our results indicate that the action selection can be dissected into specific stages, establishing the possibility to develop collusion prevention systems that are able to recognize situations which might lead to a collusion between competitors. We furthermore provide evidence for a situation where agents are capable of performing a tacit cooperation strategy without being explicitly trained to do so.Comment: accepted at the 19th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2021

Does one Creative Tool Fit All? Initial Evidence on Creativity Support Systems and Wikipedia-based Stimuli

Creativity is important to all kind of organizations, because creative capacity can help tackle complex challenges and navigate through the ambiguity of wicked problems. In Information Systems (IS) research, this topic is addressed by studies on creativity support systems (CSS). One promising approach is to provide (context related-) stimuli to individuals in order to inspire new and useful ideas. The relatedness of a stimuli, which means the degree to which a stimulus is related to a topic (i.e., to the creative task), is a vital characteristic. We investigated in the relationship between Wikipedia-based searching results (computational relatedness) and individual cognition (individual relatedness). Our initial findings show that there can be differences between individuals based on demographic variables. We further suggest a laboratory experiment in order to contribute to a CSS that takes individual relatedness and thus custom-fit stimuli into account

Detecting Mind Wandering Episodes in Virtual Realities Using Eye Tracking

Virtual Reality (VR) allows users to experience their environment differently and more immersively than traditional information systems (IS). Therefore, it is important to also study cognitive processes in VR settings. In this proposal, we focus on the concept of mind wandering, which is an emerging concept in IS research that can be studied using neurological measures such as eye tracking. Current literature suggests that mind wandering is a complex concept with different dimensions, namely deliberate and spontaneous mind wandering. While previous literature has provided initial evidence on the feasibility of eye tracking to approximate mind wandering, this study seeks to investigate how well eye tracking performs when it comes to a more nuanced perspective on mind wandering applied in an VR setting