Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution

This study presents a novel deep learning method, called GATv2-GCN, for predicting player performance in sports. To construct a dynamic player interaction graph, we leverage player statistics and their interactions during gameplay. We use a graph attention network to capture the attention that each player pays to each other, allowing for more accurate modeling of the dynamic player interactions. To handle the multivariate player statistics time series, we incorporate a temporal convolution layer, which provides the model with temporal predictive power. We evaluate the performance of our model using real-world sports data, demonstrating its effectiveness in predicting player performance. Furthermore, we explore the potential use of our model in a sports betting context, providing insights into profitable strategies that leverage our predictive power. The proposed method has the potential to advance the state-of-the-art in player performance prediction and to provide valuable insights for sports analytics and betting industries

Design and Evaluation of Intelligent Reward Structures in Human Computation Games

Despite the ubiquity of artificial intelligence, some problems and procedures— such as building commonsense knowledge understanding or generating creative works— have no or few effective algorithmic solutions, yet are considered straightforward for humans to solve. Human computation games (HCGs) are playful, game-based interfaces for tackling these problems through crowdsourcing. HCGs have been used to solve tasks that were and still are considered complex for computational algorithms such as image tagging, protein synthesis, 3D structure reconstruction, and creative artifact generation. However, despite these successes, HCGs have not seen broad adoption compared to other types of serious digital games. Among the many reasons for this lack of adoption is the reality that these games are typically not seen as engaging or compelling to play, as well as the fact that creating HCGs comes at a high development cost to task providers who are typically not game development experts. This thesis is a step towards building and establishing a more formalized design understanding of how to create HCGs that both provide a compelling player experience and complete the underlying task effectively. In this thesis, I explore reward mechanics in HCGs. Reward mechanics are integral to HCGs due their associations with player motivation, compensation, and task validation. I first propose a framework for understanding HCG mechanics and advocate for an experimental methodology evaluating both player experience and task completion metrics to understand variations in HCG mechanics. I then use these tools to frame and design three experiments that explore small-scale variations of reward systems in HCGs: reward functions, reward distribution, and reward personalization. These studies demonstrate that even small variations in rewards (i.e., offering players the ability to choose the type of reward) may have significant positive effects on both player experience and task completion metrics. I also show that some variations (i.e., co-located, competitive reward scoring) may have both positive and negative tradeoffs across these metrics. Moreover, this work observes that existing, anecdotal design wisdom for HCGs may not always hold (i.e., allowing players to verbally collude actually predicts higher task solution accuracy). Altogether, this thesis demonstrates that certain aspects of reward systems in HCGs can be varied to improve the player experience without compromising task completion metrics, and builds more empirically-tested design knowledge for creating more engaging, effective HCGs.Ph.D

Desain Interaksi Aplikasi Zero Waste dengan Menerapkan Gamifikasi Menggunakan Pendekatan Player-Centered Design

Berdasarkan Indeks Perilaku Ketidakpedulian Lingkungan Hidup (IPKLH), menunjukkan bahwa tingkat ketidakpedulian masyarakat Indonesia terhadap pengelolaan sampah masih tinggi. Salah satu cara untuk meningkatkan kepedulian adalah memberikan edukasi penerapan zero waste melalui aplikasi mobile. Desain interaksi menjadi faktor penting dalam mengembangkan aplikasi, agar efektif bagi pengguna untuk peningkatan kepedulian lingkungan. Beberapa situs web terkait zero waste yang ada cenderung menyerupai e-commerce penjualan produk zero waste dan blog. Penelitian-penelitian sebelumnya menunjukkan bahwa penerapan gamifikasi pada sebuah sistem dapat meningkatkan motivasi seseorang dalam belajar dan dapat mengubah perilakunya. Penelitian ini bertujuan untuk mengembangkan desain interaksi aplikasi zero waste guna meningkatkan motivasi masyarakat dalam menerapkan prinsip zero waste melalui penerapan gamifikasi. Pengembangan desain interaksi ini dilakukan menggunakan metode player-centered design yang dalam pengembangannya menggunakan prinsip gamifikasi dengan tahapan memahami pemain, misi, motivasi pengguna, menerapkan mekanik game, dan monitor. Fitur yang dirancang mengacu pada Taksonomi Bloom, yaitu untuk mengaplikasikan suatu hal, seseorang harus mengetahui dan memahaminya terlebih dahulu. Prototipe desain interaksi high fidelity ini dibangun untuk memenuhi usability goals yaitu effective to use dan efficient to use serta user experience goals yaitu helpful dan motivating. Ketercapaian usability goals dan user experience goals diukur secara kuantitatif menggunakan metrik Success Rate dengan skor 86,4% untuk effective to use, System Usability Scale (SUS) dengan skor 86,5 untuk efficient to use, Intrinsic Motivation Inventory (IMI) subskala value/usefulness sebesar 6,31 untuk helpful, dan IMI subskala interest/enjoyment sebesar 5,97 untuk motivating. Berdasarkan pengukuran tersebut, disimpulkan bahwa user experience goals dan usability goals dari desain interaksi ini sudah tercapai. AbstractAccording to the Environmental Indifference Behavior Index (IPKLH), the level of indifference to waste management by Indonesians is still on a high level. One way to increase awareness is to provide education towards a zero-waste lifestyle using a mobile platform. Design interaction turns into a key factor to develop the effectiveness toward application for increasing environmental indifference. Several zero waste-based websites are similar to blog and zero waste product selling e-commerce. In earlier research shows gamification applied to a system could lead to improve an individual motivation toward studying by also transform their behavior. This research intends to develop zero waste application design interaction to escalate people motivation for applying zero waste fundamental by using gamification appliance. The application is developed with a player-centered design approach, using gamification principles to increase user motivation, starts with understanding the players, the mission, the motivation, defining the game mechanics, and monitoring. The features designed in the application refer to Bloom's Taxonomy, which states that to be able to apply something, one must know and understand it. The output of this project is a high-fidelity prototype that meets several usability goals and user experience goals. The usability goals are effective to used and efficient to use, and the user experience goals are helpful and motivating. Using the success rate metric, the result of the measurement for effectivity goal is 86.4%. For the efficiency goal, the result of the measurement using the System Usability Score (SUS) metric is 86.5. Using the Intrinsic Motivation Inventory, the score for the value/usefulness subscale for helpful goal is 6.31 and for the interest/enjoyment subscale is 5.97 for the motivating goal. Based on these measurements, it can be concluded that this application has achieved the user experience goals and usability goals

Consumer Preference on Paid Game Microtransaction

Online gaming has become prevalent with the rise of the internet availability, where the gaming industry is experiencing a shift in business model in the last decade. The new model of microtransaction is to make players pay for extra content and advantages to compete against other players. In this paper, we aim at finding out what the consumer preference on microtransaction in paid game. Mode, Price, Genre, Microtransaction, and Payment Method are the preferences used as benchmark for this research that influences decision making for players. To better understand the characters of the players, cluster analysis is used to group players who have similar preferences with their respective preferences

Data-Driven Analysis towards Monitoring Software Evolution by Continuously Understanding Changes in Users’ Needs

Ohjelmistot eivät usein vastaa käyttäjiensä odotuksia siitä huolimatta, että niiden odotetaan tarjoavan riittävä toiminnallisuus ja olevan virheettömiä. Tästä syystä ohjelmiston ylläpito on väistämätöntä ja tärkeää jokaiselle ohjelmistoyritykselle, joka haluaa pitää tuotteensa tai palvelunsa kannattavana. Koska kilpailu nykyajan ohjelmistomarkkinoilla on tiukkaa ja käyttäjien on helppo lopettaa tuotteen käyttö, yritysten on erityisen tärkeää tarkkailla ja ylläpitää käyttäjätyytyväisyyttä pitkäaikaisen menestyksen turvaamiseksi. Tämän saavuttamiseksi tärkeää on jatkuvasti ymmärtää ja kohdata käyttäjien tarpeet ja odotukset, sillä on tehokkaampaa kohdentaa ylläpito käyttäjien esittämien ongelmien perusteella. Toisaalta internet-teknologiat ovat kehittyneet nopeasti samalla, kun käyttäjien luoman sisällön määrä on kasvanut räjähdysmäisesti. Käyttäjien antama palaute (numeerinen arvostelu, ehdotus tai tekstuaalinen arvio) on esimerkki tällaisesta käyttäjien luomasta sisällöstä ja sen merkitys tuotteiden kehittämisessä asiakkaiden tarpeiden pohjalta kasvaa jatkuvasti. Käyttäjien tarpeiden ymmärtäminen on erityisen tärkeää jatkuvaa ylläpitoa ja kehitystystä vaativissa ohjelmistoissa. Tällöin on myös oleellista ymmärtää, miten asiakkaiden mielipiteet muuttuvat ajan kuluessa. Tämän lisäksi datan louhimisen ja koneoppimisen kehitys vähentävät vaivaa, joka käyttäjän tuottaman datan analysointiin ja erityisesti heidän käyttymisensä ymmärtämiseen tarvitaan. Vaikka useat tutkimukset ehdottavat tietokeskeistä lähestymistä palautteen arvioin- tiin, ohjelmiston ylläpitoa ja kehitystä hyödyntäviä lähestymistapoja on vähän. Monet menetelmät keskittyvät arvostelujen analysoinnissa tekstinlouhintaan paljastaakseen käyttäjien mielipiteet. Useat menetelmät keskittyvät myös tunnistamaan ja luokit- telemaan palautetyyppejä kuten ominaisuuspyyntöjä, virheilmoituksia ja tunteenilmauksia. Jotta ohjelmiston ylläpidosta saataisiin tehokkaampaa, tarvitaankin tehokas lähestymistapa ohjelmiston havaitun käyttäjäkokemuksen ja sen muutosten tarkkailuun ohjelmiston kehittyessä.Software products, though always being expected to provide satisfactory functionalities and be bug-free, somehow fail to meet the expectations of their users. Thus, software maintenance is inevitable and critical for any software companies who want their products or services to continue profiting. On the other hand, due to the fierce competitiveness in the contemporary software market, as well as the ease of user churns, monitoring and sustaining the satisfaction of the users is a critical criterion for the long-term success of any software products within their evolution stage. To such an end, continuously understanding and meeting the users’ needs and expectations is the key, as it is more efficient and effective to allocate maintenance effort accordingly to address the issues raised by users. On the other hand, accompanied by the rapid development of internet technologies, the volume of user-generated content has been increasing exponentially. Among such user-generated content, feedback from the customers, either numeric rating, recommendation, or textual reviews, have been playing an increasingly critical role in product designs in terms of understanding customers’ needs. Especially for software products that require constant maintenance and are continuously evolving, understanding of users’ needs and complaints, as well as the changes in their opinions through time, is of great importance. Additionally, supported by the advance of data mining and machine learning techniques, the effort of knowledge discovery from analyzing such data and specially understanding the behavior of the users shall be largely reduced. However, though many studies propose data-driven approaches for feedback analysis, the ones specifically on applying such methods supporting software maintenance and evolution are limited. Many studies focus on the text mining perspective of review analysis towards eliciting users’ opinions. Many others focus on the detection and classification of feedback types, e.g., feature requests, bug reports, and emotion expression, etc. For the purpose of enhancing the effectiveness in soft ware maintenance and evolution practice, an effective approach on the software’s perceived user experience and the monitoring of its changes during evolution is re- quired. To support the practice of software maintenance and evolution targeting enhancing user satisfaction, we propose a data-driven user review analysis approach. The contribution of this research aims to answer the following research questions: RQ1. How to analyze users’ collective expectation and perceived quality in use with data- driven approaches by exploiting sentiment and topics? RQ2. How to monitor user satisfaction over software updates during software evolution using reviews’ topics and sentiments? RQ3. How to analyze users’ profiles, software types and situational contexts as contexts of use that supports the analysis of user satisfaction? Towards answering RQ1, the thesis proposes a data-driven approach of user perceived quality evaluation and users’ needs extraction via sentiment analysis and topic modeling on large volume of user review data. Based on such outcome, the answer to RQ2 encompasses of 1) the approach to monitor user opinion changes through software evolution by detecting similar topic pairs and 2) the approach to identify the problematic updates based on anomalies in review sentiment distribution. Towards the answer to RQ3, a three-fold analysis is proposed: 1) situational contexts and ways of interaction analysis, 2) user profile and preference analysis and 3) software type and related features analysis. All the above approaches are validated by case studies. This thesis contributes to the examination of applying data-driven end user re- view analysis methods supporting software maintenance and evolution. The main implication is to enrich the existing domain knowledge of software maintenance and evolution in terms of taking advantage of the collective intelligence of end users. In addition, it conveys unique contribution to the research on software evolution con- texts in terms of various meaningful aspects and leads to a potential interdisciplinary contribution as well. On the other hand, this thesis also contributes to software maintenance and evolution practice even in the larger scope of the software industry by proposing an effective series of approaches that address critical issues within. It helps the developers ease their effort in release planning and other decision-making activities

Modes of Esports Engagement in Overwatch

This Open Access book provides a comprehensive review of the rapidly developing esport phenomenon by examining one of its contemporary flagship titles, Overwatch (Blizzard Entertainment 2016), through three central themes and from a rich variety of research methods and perspectives. As a game with more than 40 million individual players, an annual international World Cup, and a franchised professional league with teams from Canada, China, Europe, South Korea, and the US, Overwatch provides a multifaceted perspective to the cultural, social, and economic topics associated with the development of esports, which has begun to attract attention from both commercial and academic audiences. The book starts with an introduction chapter to Overwatch and esports engagement in general, co-authored by the editors. This is followed by 15 unique chapters from scholars within the field of game cultures and esports, representing ten different nationalities. The contributions construct thematic sections that divide the book into three parts: Players, Diverse Audiences? and Fan & Fiction Work. As such, the parts provide a wide-ranging overview of esport engagement, thus disclosing the phenomenon’s cross-cultural, transmedial, and interconnected relations that have not been probed earlier in a single anthology

Modes of Esports Engagement in Overwatch

This Open Access book provides a comprehensive review of the rapidly developing esport phenomenon by examining one of its contemporary flagship titles, Overwatch (Blizzard Entertainment 2016), through three central themes and from a rich variety of research methods and perspectives. As a game with more than 40 million individual players, an annual international World Cup, and a franchised professional league with teams from Canada, China, Europe, South Korea, and the US, Overwatch provides a multifaceted perspective to the cultural, social, and economic topics associated with the development of esports, which has begun to attract attention from both commercial and academic audiences. The book starts with an introduction chapter to Overwatch and esports engagement in general, co-authored by the editors. This is followed by 15 unique chapters from scholars within the field of game cultures and esports, representing ten different nationalities. The contributions construct thematic sections that divide the book into three parts: Players, Diverse Audiences? and Fan & Fiction Work. As such, the parts provide a wide-ranging overview of esport engagement, thus disclosing the phenomenon’s cross-cultural, transmedial, and interconnected relations that have not been probed earlier in a single anthology

Self-adaptive Authorisation Infrastructures

Traditional approaches in access control rely on immutable criteria in which to decide and award access. These approaches are limited, notably when handling changes in an organisation’s protected resources, resulting in the inability to accommodate the dynamic aspects of risk at runtime. An example of such risk is a user abusing their privileged access to perform insider attacks. This thesis proposes self-adaptive authorisation, an approach that enables dynamic access control. A framework for developing self-adaptive authorisation is defined, where autonomic controllers are deployed within legacy based authorisation infrastructures to enable the runtime management of access control. Essential to the approach is the use of models and model driven engineering (MDE). Models enable a controller to abstract from the authorisation infrastructure it seeks to control, reason about state, and provide assurances over change to access. For example, a modelled state of access may represent an active access control policy. Given the diverse nature in implementations of authorisation infrastructures, MDE enables the creation and transformation of such models, whereby assets (e.g., policies) can be automatically generated and deployed at runtime. A prototype of the framework was developed, whereby management of access control is focused on the mitigation of abuse of access rights. The prototype implements a feedback loop to monitor an authorisation infrastructure in terms of modelling the state of access control and user behaviour, analyse potential solutions for handling malicious behaviour, and act upon the infrastructure to control future access control decisions. The framework was evaluated against mitigation of simulated insider attacks, involving the abuse of access rights governed by access control methodologies. In addition, to investigate the framework’s approach in a diverse and unpredictable environment, a live experiment was conducted. This evaluated the mitigation of abuse performed by real users as well as demonstrating the consequence of self-adaptation through observation of user response