Examining the Social Interactions of Young Adults with Autism Spectrum Disorders in a Virtual Environment

This phenomenological study examined the social interactions during online game play in a virtual environment for five young adults with an autism spectrum disorder (ASD) who attended a large metropolitan university, enrolled in the first 60 credits of a science, technology, engineering, or mathematics (STEM) field of study. Given the evolution of technology and opportunities to socialize in virtual communities, it is becoming increasingly important to understand how young adults with ASD assimilate into new social opportunities that provide supports for extraneous variables such as face-to-face situations. As research begins to emerge on virtual environments there is little research addressed specific to socialization and the development of interpersonal relationships. Further, there is a distinct lack of research specific to young adults with ASD who engage socially in virtual environments. A phenomenological research method was used to explain the social activities as they occurred for this specific group of individuals. Structured and unstructured interviews, observations, document analysis, and a self-reporting survey were conducted and collected. Analysis used emergent coding following Moustakas* modified Van Kaam method (1994). Common themes were identified and reported through lists and tables. In summary, this study described how young adults with ASD socialized within a virtual community. This study provided findings that individuals with ASD actively seek friendships, recognize emotions, understand roles within the game and real life use skills necessary for success in postsecondary education and STEM related careers, and lays the foundation for continuing research using virtual environments to support interpersonal relationships that may support greater postsecondary outcomes

MMORPG-pelaajan pelin lopettamisen ennustaminen koneoppimisella

Massiiviset monen pelaajan verkkoroolipelit eli MMORPG-pelit (eng. Massively Multiplayer Online Role-playing Game) ovat suosittuja verkossa pelattavia pelejä, joiden tunnusmerkkejä ovat fantasiapainotteinen roolipelaaminen sekä jaetussa pelimaailmassa pelaaminen. Verkkopelaamisen harrastajamäärät ovat jatkuvassa kasvussa, ja suosituilla MMORPG-peleillä on miljoonia pelaajia. Peliyhtiöt kilpailevat pelaajien ajasta ja sitoutumisesta, ja ovat valmiita muokkaamaan peliä potentiaalisia pelaajia houkuttelevaksi. Tässä tutkimuksessa ennustetaan koneoppimistekniikoita käyttämällä suositun MMORPG-pelin potentiaalisista pelaajista ne, jotka tulevat lopettamaan pelin pelaamisen tulevaisuudessa. Peliyhtiöille on tärkeää pystyä tunnistamaan pelaajia, joiden kiinnostus peliä kohtaan on laskemassa, jo ennen kuin pelaaja varsinaisesti lopettaa pelaamisen. Näin peliyhtiöt voivat pyrkiä pitämään pelaajaa pelin parissa tarjoamalla pelaajalle esimerkiksi houkuttimia tai helpotusta pelaamiseen. Lopettavien pelaajien tunnistaminen auttaa myös peliyhtiöitä pelin kehittämisessä ja peliyhtiöt voivat yrittää poistaa peleistään sellaisia ominaisuuksia, jotka nostavat pelaajien pelin lopettamisen todennäköisyyttä. Pelkkä tieto siitä, ketkä tulevat lopettamaan pelin pelaamisen, ei siis riitä. Peliyhtiöitä kiinnostaa myös se, millä tavalla pelin lopettavat pelaajat eroavat pelaajista, joiden motivaatio peliä kohtaan on säilynyt. Tutkimuksen data on peräisin IEEE:n 2017 isännöimästä pelindatanlouhintakilpailusta, ja tutkimuksessa tutkitaan kilpailussa menestyneiden joukkueiden kilpailutöitä. Tutkimuksessa pyritään parantamaan Turun yliopiston (UTU) kilpailujoukkueen kilpailutyön ennustustarkkuutta lisäämällä malliin uusia piirteitä. Älykkäät piirteet vähentämät malliin tarvittavien piirteiden määrää. Tutkimuksessa tutkittiinkin yli sataa potentiaalista piirrettä, joista 40 valittiin uuteen malliin sovitettavaksi. Uusien piirteiden, sekä tiimi UTU:n mittaamien piirteiden, toimivuutta mitattiin usealla tekniikalla, joista parhaimman ristiinvalidointitarkkuuden saavuttivat harjanneluokittelija, lineaarinen tukivektorikone ja logistinen regressio. Testidatojen validoinnissa logistinen regressio onnistui parantamaan tiimin kilpailuratkaisua eniten. Parhaiten menestyneessä mallissa oli vain yksitoista piirrettä, joista viisi oli uusia piirteitä ja kuusi sisältyi myös tiimi UTU:n kilpailutyöhön. Sekä tämän tutkimuksen, että varsinaisessa kilpailussa toiseksi päätyneen tiimi UTU:n ratkaisu, poikkeavat merkittävästi kilpailun voittajajoukkueen Yokozuna Data:n mallista. Voittajajoukkue käytti mallissaan jopa 500 piirrettä ja monimutkaisia tekniikoita, kuten syväoppimista ja satunnaistettuja päätöspuita. Koska molemmat lineaarista mallia käyttävät ratkaisut päätyivät melkein samaan tulokseen kuin voittajajoukkueen malli, tutkimuksesta käy ilmi, että juuri älykäs piirteiden valinta on avainasemassa MMORPG-pelin pelaajien lopettamisen ennustamisessa ja että lopettavat pelaajat voi ennustaa hyvin pienellä määrällä piirteitä

‘Hanging with the ‘Cathaby Shark Gurlz’ and other Runescape stories: Young people, identity and community in a virtual world

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.In this research I offer a five year ethnographically informed participative observation of a popular virtual space. I explore the practices of young people within the virtual world of the online gaming community of „Runescape‟. I consider how its‟ young citizens construct and maintain virtual „self‟ within virtual social systems, and how social groups and communities emerge and develop. These are popular virtual spaces and such games occupy an important place in the leisure lives of many young people. I examine how those identities interact with the virtual environment and the structures and institutions that are developed to allow groups and individuals to operate within its „culture‟. I suggest that the distinction between virtual and material „existence‟ is not clear-cut and oppositional but porous and mutually defining – a shifting dynamic rather than a rigid division. However, virtuality is no „liberated space‟ and it incorporates norms and practices that often mirror those of the material world. Online games, particularly the virtual worlds of role-playing games, sit at the interface between these two planes. The virtual world of online games offers young people a „spectacular space‟ – in some ways similar to other public spaces yet simultaneously quite different – in which they can undertake creative identity work and symbolic experimentation with many of the institutions, rituals and practices that they encounter within their material worlds. Importantly, game worlds have a particular capacity in enabling participants to interact with others in a form mediated by the game itself. Thus new possibilities for communion are made possible. This, I argue, makes these games potentially powerful settings for young people to exercise agency in marking out and playing with identity and other social processes, particularly when many of the material arenas within which such activities have traditionally been practiced are becoming increasingly denied to modern youth. I argue that virtual space provides young people with a „safe‟ arena to explore many material processes, and in this sense is an „ordinary space‟ like many of the others in which they operate. However, the use of avatars also permits young people to appear in a form chosen by them. Thus, in the virtual world, „material‟ cultural codes of body and conduct constituted by gender, class and race can, apparently, be effaced, opening up interesting, creative and potentially resistive possibilities for participants. I argue therefore that, online gaming is an important and somewhat under-researched space in which young people engage in new practices of „leisure and pleasure‟

Modeling Human Group Behavior In Virtual Worlds

Virtual worlds and massively-multiplayer online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. They provide new outlets for human social interaction that differ from both face-to-face interactions and non-physically-embodied social networking tools such as Facebook and Twitter. We aim to study group dynamics in these virtual worlds by collecting and analyzing public conversational patterns of users grouped in close physical proximity. To do this, we created a set of tools for monitoring, partitioning, and analyzing unstructured conversations between changing groups of participants in Second Life, a massively multi-player online user-constructed environment that allows users to construct and inhabit their own 3D world. Although there are some cues in the dialog, determining social interactions from unstructured chat data alone is a difficult problem, since these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. Humans are adept social animals capable of identifying friendship groups from a combination of linguistic cues and social network patterns. But what is more important, the content of what people say or their history of social interactions? Moreover, is it possible to identify whether iii people are part of a group with changing membership merely from general network properties, such as measures of centrality and latent communities? These are the questions that we aim to answer in this thesis. The contributions of this thesis include: 1) a link prediction algorithm for identifying friendship relationships from unstructured chat data 2) a method for identifying social groups based on the results of community detection and topic analysis. The output of these two algorithms (links and group membership) are useful for studying a variety of research questions about human behavior in virtual worlds. To demonstrate this we have performed a longitudinal analysis of human groups in different regions of the Second Life virtual world. We believe that studies performed with our tools in virtual worlds will be a useful stepping stone toward creating a rich computational model of human group dynamics

Game analytics - maximizing the value of player data

During the years of the Information Age, technological advances in the computers, satellites, data transfer, optics, and digital storage has led to the collection of an immense mass of data on everything from business to astronomy, counting on the power of digital computing to sort through the amalgam of information and generate meaning from the data. Initially, in the 1970s and 1980s of the previous century, data were stored on disparate structures and very rapidly became overwhelming. The initial chaos led to the creation of structured databases and database management systems to assist with the management of large corpuses of data, and notably, the effective and efficient retrieval of information from databases. The rise of the database management system increased the already rapid pace of information gathering.peer-reviewe

What World of Warcraft is Teaching Us About Learning.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Mining Social Interaction Data in Virtual Worlds

Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. This chapter presents techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world