Real-time adaptive track generation in racing games

Real-time Adaptive Track Generation in Racing Game

A framework for quantitative analysis of user-generated spatial data

This paper proposes a new framework for automated analysis of game-play metrics for aiding game designers in finding out the critical aspects of the game caused by factors like design modications, change in playing style, etc. The core of the algorithm measures similarity between spatial distribution of user generated in-game events and automatically ranks them in order of importance. The feasibility of the method is demonstrated on a data set collected from a modern, multiplayer First Person Shooter, together with application examples of its use. The proposed framework can be used to accompany traditional testing tools and make the game design process more efficient

Problematising upstream technology through speculative design: the case of quantified cats and dogs

There is growing interest in technology that quantifies aspects of our lives. This paper draws on critical practice and speculative design to explore, question and problematise the ultimate consequences of such technology using the quantification of companion animals (pets) as a case study. We apply the concept of ‘moving upstream’ to study such technology and use a qualitative research approach in which both pet owners, and animal behavioural experts, were presented with, and asked to discuss, speculative designs for pet quantification applications, the design of which were extrapolated from contemporary trends. Our findings indicate a strong desire among pet owners for technology that has little scientific justification, whilst our experts caution that the use of technology to augment human-animal communication has the potential to disimprove animal welfare, undermine human-animal bonds, and create human-human conflicts. Our discussion informs wider debates regarding quantification technology

Player superstition as a design resource

This paper discusses superstitious behaviour in game play, explains that superstition is a natural component of learning, suggest strategies for harnessing player superstition as a design resource, and presents a case study of a game, Non-League Football Supporter, which uses player superstition as the core mechanic

Visualising player data for video game designers

The collection and analysis of videogame players' actions in the game world, known as game telemetry, is a common technique for understanding the behaviour of players. This process, known as Game Analytics, often uses data visualisation to allow designers to manually analyse features of the data. Heatmap visualisation, a grid-based visualisation showing how often an event occurs across the game world (e.g. �ring of weapons), is used widely in the games industry for visualising aggregated data, but has limitations when used to classify player behaviour at an individual or group level. Existing works using clustering to identify player behaviour yield results that must be interpreted by an expert, a problem acknowledged by existing research. Motivated by these limitations, this work presents the novel application of dendrogram visualisation as a means to interpret large datasets of heatmaps, through the use of hierarchical clustering, to aid designers in exploring and analysing player behaviour. This allows an intuitive and well- understood visualisation technique (heatmaps) to be used for cluster analysis, presenting intelligible results to a game designer, in a format they are familiar with. To evaluate dendrograms as a design tool, a system was designed and implemented to visualise player data, using heatmaps, with hierarchical clustering being performed on these heatmaps, the results displayed as a dendrogram. A feasibility study was con- ducted with a set of game designers, to understand the opportunities and limitations of dendrograms as a game analytics tool. The results a�rmed the utility of heatmaps for visualising aggregate data, but visual complexity increases in large quantities. Den- drograms were found to be initially di�cult to read, but showed promise for analysing large sets of data and guiding the designer to interesting areas of the data, provided they could \drill down" into the base data (heatmaps). In light of these �ndings, a us- ability study was designed and conducted with a set of 40 game development students, where they were presented with realistic game design scenarios, and asked to �nd an- swers to analytics questions using heatmaps and dendrograms. The results showed that whilst dendrograms were initially di�cult to understand, they were used to successfully explore and understand cluster relationships, with participants providing the correct answers grounded in the data. Furthermore participants reiterated the need to explore the base data (heatmaps) to understand the cluster relationships of the dendrogram. This work concludes that dendrograms represent a viable and useful tool for identifying interesting behaviour patterns within a heatmap dataset. Whilst some familiarity is required with the tool, it is possible to use dendrograms to explore behaviour clusters within a large dataset, and this work presents a solution to the limitations of analysing player behaviour through the use of heatmaps in large datasets. This work highlights a number of avenues for future work, such as deploying and studying dendrograms in a game production setting, or evaluating the dendrogram visualisation in di�erent game genres

An Augmented Reality Game using Face Recognition Technology

In this paper, we explore the coupling of mobile facial recognition technology with the exploitation of non-players as a powerful mechanic in locative augmented reality games. A prototype game is presented which asks players to "capture" the likeness of members of the public. Driven by free-to-play models, and inspired by the phenomenal success of Pokémon GO, we have created an experience where players hunt for and "capture" real creatures in a real world

Managing Multiple Identities to Combat Stigmatisation in the Digital Age

It has long been identified that people consciously curate, manage and maintain multiple online individual identities based on characteristics such as race, gender, and societal status; research has also established that people may choose to emphasise one such identity other another as a means to avoid stigmatisation, discrimination and stereotyping. The rise of online state, corporate, and peer surveillance however threatens to disrupt this process by modelling, categorising and restraining identity to that which has been surveilled. We posit that new anti-surveillance tactics may emerge that allow users the freedom to manage and switch their identities in ways that seek to maintain social justice and counteract discrimination

Problematising upstream technology through speculative design: the case of quantified cats and dogs

There is growing interest in technology that quantifies aspects of our lives. This paper draws on critical practice and speculative design to explore, question and problematise the ultimate consequences of such technology using the quantification of companion animals (pets) as a case study. We apply the concept of "moving upstream" to study such technology and use a qualitative research approach in which both pet owners, and animal behavioural experts, were presented with, and asked to discuss, speculative designs for pet quantification applications, the design of which were extrapolated from contemporary trends. Our findings indicate a strong desire among pet owners for technology that has little scientific justification, whilst our experts caution that the use of technology to augment human-animal communication has the potential to disimprove animal welfare, undermine human-animal bonds, and create human-human conflicts. Our discussion informs wider debates regarding quantification technology

Chatbots for social good

Chatbots are emerging as an increasingly important area for the HCI community, as they provide a novel means for users to interact with service providers. Due to their conversational character, chatbots are potentially effective tools for engaging with customers, and are often developed with commercial interests at the core. However, chatbots also represent opportunities for positive social impact. Chatbots can make needed services more accessible, available, and affordable. They can strengthen users' autonomy, competence, and (possibly counter-intuitively) social relatedness. In this SIG we address the possible social benefits of chatbots and conversational user interfaces. We will bring together the existing, but disparate, community of researchers and practitioners within the CHI community and broader fields who have an interest in chatbots. We aim to discuss the potential for chatbots to move beyond their assumed role as channels for commercial service providers, explore how they may be used for social good, and how the HCI community may contribute to realize this.acceptedVersio