Exploiting General-Purpose In-Game Behaviours to Predict Players Churn in Gameful Systems

The value of a game is assessed by measuring the intensity of the level of activity of its players. No matter how thoroughly though the design is, the litmus test is whether players keep using it or not. To reduce the number of abandoning players, it is important to detect in time the subjects at risk. In the literature, many works are targeting this issue. However, the main focus has been on entertainment games, from which articulated indicators of in-game behaviors can be extracted. Those features tend to be context-specific and, even when they are not, they are proper of full-featured games, and thus, impossible to adapt to other systems such as games with a purpose and gamified apps. In this preliminary work, we fed to an Artificial Neural Network general-purpose in-game behaviors, such as participation data, to predict when a player will definitively leave the game. Moreover, we study the appropriate amount of information, in terms of players’ history, that should be considered when predicting players’ churn. Our use case study is an on-the-field long-lasting persuasive gameful system

ATLAS: A new way to exploit world-wide mobility services

Abstract Despite the extent of the ecosystem of mobility services and the disparate functionalities they offer, organizing journeys by properly exploiting them and enhancing their interoperability is still a complex task. Moreover, the high degree of dynamicity characterizing modern service-based systems requires to make them able to self-adapt at runtime. In this paper, we present ATLAS , a world-wide travel assistant able to provide accurate and context-aware traveling solutions, supporting users for the whole travel duration. ATLAS has been realized by exploiting a tool to engineer adaptive by design service-based systems operating in open and dynamic environments

Dynamic adaptation of service-based applications: a design for adaptation approach

Abstract A key challenge posed by the Next Generation Internet landscape is that modern service-based applications need to cope with open and continuously evolving environments and to operate under dynamic circumstances (e.g., changes in the users requirements, changes in the availability of resources). Indeed, dynamically discover, select and compose the appropriate services in such environment is a challenging task. Self-adaptation approaches represent effective instruments to tackle this issue, because they allow applications to adapt their behaviours based on their execution environment. Unfortunately, although existing approaches support run-time adaptation, they tend to foresee the adaptation requirements and related solutions at design-time, while working under a "closed-world" assumption. In this article our objective is that of providing a new way of approaching the design, operation and run-time adaptation of service-based applications, by considering the adaptivity as an intrinsic characteristic of applications and from the earliest stages of their development. We propose a novel design for adaptation approach implementing a complete lifecycle for the continuous development and deployment of service-based applications, by facilitating (i) the continuous integration of new services that can easily join the application, and (ii) the operation of applications under dynamic circumstances, to face the openness and dynamicity of the environment. The proposed approach has been implemented and evaluated in a real-world case study in the mobility domain. Experimental results demonstrate the effectiveness of our approach and its practical applicability

Do Influencers Influence? -- Analyzing Players' Activity in an Online Multiplayer Game

In social and online media, influencers have traditionally been understood as highly visible individuals. Recent outcomes suggest that people are likely to mimic influencers' behavior, which can be exploited, for instance, in marketing strategies. Also in the Games User Research field, the interest in studying player social networks has emerged due to the heavy reliance on online influencers in marketing campaigns for games, as well as in keeping players engaged. Despite the inherent value of those individuals, it is still difficult to identify influencers, as the definition of influencers is a debated topic. Thus, how can we identify influencers, and are they indeed the individuals impacting others' behavior? In this work, we focus on influence in retention to verify whether central players impacted others' permanence in the game. We identified the central players in the social network built from the competitive player-vs-player (PvP) multiplayer (Crucible) matches in the online shooter Destiny. Then, we computed influence scores for each player evaluating the increase in similarity over time between two connected individuals. In this paper, we were able to show the first indications that the traditional metrics for influencers do not necessarily apply for games. On the contrary, we found that the group of central players was distinct from the group of influential players, defined as the individuals with the highest influence scores. Then, we provide an analysis of the two groups.Comment: accepted for publication in IEEE Conference on Games (CoG) 202

Virtual coaches for mission-based gamified smart communities.

We propose a Virtual Coach for the gamification of participatory applications in complex socio-technical systems like Smart Cities and Smart Communities. In such participatory applications, the user community is an active and essential component. Users must voluntarily take up some tasks, in order to ensure the correct operation of the application according to its requirements and goals, which, in turn, delivers collective benefits to the community. In order to facilitate users, and support their sustained engagement in a participatory application, we use a Missions metaphor to describe those volunteering tasks. Our Virtual Coach is then responsible for selecting and recommending missions to users, based on a variety of factors, including the criticality of the corresponding tasks for the application purposes, the importance of the task for the individual user that should take it up, user profile characteristics, like personal preferences and skills, and the in-game incentives the user would earn by completing the mission

A context-aware framework for dynamic composition of process fragments in the internet of services

Abstract In the last decade, many approaches to automated service composition have been proposed. However, most of them do not fully exploit the opportunities offered by the Internet of Services (IoS). In this article, we focus on the dynamicity of the execution environment, that is, any change occurring at run-time that might affect the system, such as changes in service availability, service behavior, or characteristics of the execution context. We indicate that any IoS-based application strongly requires a composition framework that supports for the automation of all the phases of the composition life cycle, from requirements derivation, to synthesis, deployment and execution. Our solution to this ambitious problem is an AI planning-based composition framework that features abstract composition requirements and context-awareness. In the proposed approach most human-dependent tasks can be accomplished at design time and the few human intervention required at run time do not affect the system execution. To demonstrate our approach in action and evaluate it, we exploit the ASTRO-CAptEvo framework, simulating the operation of a fully automated IoS-based car logistics scenario in the Bremerhaven harbor

Turning Users\u27 In-Game Behaviours into Actionable Adaptive Gamification Strategies using the PEAS Framework

Adaptive gamification answers the need to customize engagement strategies because users are motivated by different game elements and mechanics. To better understand these individual preferences, user modelling is vital. However, gameful designers must make many decisions on matching profiling data to actual adaptation strategies, which makes modelling particularly challenging. The lack of a standardized and guided process for adaptive gamification hinders replicability, comparability, and complicates making adaptation dynamic. In this study, we analyzed a persuasive gameful application (Play\&Go) to show how in-game behaviours can be translated into adaptation strategies. We used an existing adaptation framework (PEAS) grounded in the games and gamification literature. Our work demonstrates the suitability of the PEAS model as a shared, standardized method for adaptive gamification and shows how it can guide the process of transforming user behaviours into actionable adaptation strategies

Turning Users' In-Game Behaviours into Actionable Adaptive Gamification Strategies using the PEAS Framework

Adaptive gamification answers the need to customize engagement strategies because users are motivated by different game elements and mechanics. To better understand these individual preferences, user modelling is vital. However, gameful designers must make many decisions on matching profiling data to actual adaptation strategies, which makes modelling particularly challenging. The lack of a standardized and guided process for adaptive gamification hinders replicability, comparability, and complicates making adaptation dynamic. In this study, we analyzed a persuasive gameful application (Play\&Go) to show how in-game behaviours can be translated into adaptation strategies. We used an existing adaptation framework (PEAS) grounded in the games and gamification literature. Our work demonstrates the suitability of the PEAS model as a shared, standardized method for adaptive gamification and shows how it can guide the process of transforming user behaviours into actionable adaptation strategies

ВИБІР СЕМАНТИЧНОГО ВЕБ-СЕРВІСУ НА РІВНІ ПРОЦЕСУ: НА ПРИКЛАДІ EBAY/AMAZON/PAYPAL / ПЕРЕКЛАД СТАТТІ «SEMANTICWEB SERVICE SELECTION AT THE PROCESS-LEVEL: THE EBAY/AMAZON/PAYPAL CASE STUDY» (ПЕРЕКЛАД РЕМАРОВИЧ С.)

У цій статті ми представляємо підхід до вибору сервісу на рівні процесу та оцінки його на реальній ситуації, що спричиняє високий рівень складності: eBay Веб-сервіси, Amazon E-Commerce сервіси та сервіс e-payment, запропонований PayPal. Підхід заснований на представленні сервісів на рівні процесу, тобто на BPEL і WSDL специфікаціях, і який розширює ці стандартні специфікації мінімальними семантичними анотаціями, які дозволяють виконувати ефективні, але все ж корисні, семантичні міркування для вибору Веб-сервісів на рівні процесу

Generating Personalized Challenges to Enhance the Persuasive Power of Gamification

While gamification is often effective in incentivizing behavioral changes, well-known limitations concern retaining the interest of players over the long term, and sustaining the new behaviors promoted through the game. To make the gamification user experience more varied and compelling, we propose an approach based on the Procedural Content Generation of personalized and contextualized playable units that appeal individually to each player. We have implemented this approach as a system that generates and recommends personalized challenges, based on the player’s preference, history, game state and performance, and we have evaluated it using a smart urban mobility game that proposed weekly challenges to hundreds of citizens/players