Goodbye, [Microsoft/Sony]… Hello, [Microsoft/Sony]: An investigation into the information behaviour of console gamers when looking to purchase a new console

Purpose: The purpose of this research is to investigate the information behaviour of console gamers in the specific task of buying a new console. This takes place in two sections: firstly, to investigate the types of resources used and, secondly, to develop a picture of how four specific theories of information behaviour - Ellis’ Model of Information-Seeking Behaviour, Erdelez’s Information Encountering, Fisher’s Information Grounds and Jaeger and Burnett’s Information Worlds - may serve to provide an understanding of the behaviour exhibited. Design, methodology and approach: A questionnaire was designed and distributed via Twitter and Facebook, in which the research questions were addressed. In addition, this questionnaire served as a means of gathering participants for follow-up interviews in which the specified theories were investigated. Findings: The finding of this paper is that whilst gamers as a whole value a range of formal and informal information resources, their specific information behaviour may be attributed of their categorisation of gamer type. Furthermore, depending on this categorisation, the behaviour exhibited may be understood in terms of one or other of the aforementioned theories. Originality and value: Theories and papers which investigate information behaviour are common, whilst the subset of information behaviour of gamers is less so, but it is a rich field of study. Studies into the information behaviour of gamers which focus on the information need of consoles when a new console is looking to be purchased, however, are limited in their number, and what papers there are represent a resource to be used - ie a review of consoles - rather than an investigation into how the resources themselves are utilised. This paper provides an overview of the types of resources used by gamers and suggests how existing theories of information behaviour might help to explain this behaviour, and may be considered a platform for further investigation

Girls, Guys and Games: How News Media Perpetuate Stereotypes of Male and Female Gamers

Despite the sheer popularity of gaming, stereotypes of gamers are persistent and often ill-informed. The average age of an Australian gamer, for example, is 33 and nearly half of gamers are female. Yet, few mainstream and gaming news articles seem to acknowledge this diversity. Because news media and public perception are intertwined, such misrepresentation may affect the way gamers are perceived by the public and, in turn, how gamers negotiate their identities.This paper, through a primarily qualitative analysis of 75 online news articles, explores many examples of simplistic and distorted portrayals of gamers that characterise news coverage. In particular, it examines three gendered tropes—‘not real’ female gamers, women as the victims and oppressors of gamers, and toxic male gamers—that news media use to frame the narratives that misrepresent gaming in social life.Ultimately, this article argues that two prevailing themes underlie many news stories about gaming: the perpetuation of male technocratic privilege and moral panic. Both of these phenomena have relevance to the #GamerGate controversy of 2014, which news media portrayed as a ‘culture war’ between these inaccurate notions of male and female gamers. Thus, this indicates that the media blame game and alienation of gaming culture, as a multibillion-dollar international industry of increasing social importance, must be acknowledged and addressed

The role of badges to spur frequent travelers to write online reviews

Purpose: Online travel reviews platforms have become innovative information systems also due to the incorporation of sophisticated gamification elements such as visually appealing badges. This study aims to analyze three features of the review after leveling up a badge: review length (number of words), sentiment scoring, and period between two successive reviews (number of days until the next review is written). Design/methodology/approach: A total of 77k online TripAdvisor reviews written by 100 frequent travelers and contributors are analyzed using a data mining approach. A data-based sensitivity analysis (DSA) is then conducted to provide an understanding of the data mining trained models. Findings: The results show evidence that badges appealing for self-pride (“badge passport”) and for peer-recognition (“badge helpful”) have significant influence across the lifespan of online review, whereas badges simply awarded by counting the contributions have little effect. Originality: This study provides the first analysis of how an experienced traveler is influenced as the badges and points are being awarded. Intrinsic motivational factor to award badges for standard contributions scarcely influence user behavior. Badges need to be designed to reward accomplishments that are not so trivial to be achieved and that do not depend entirely on the user.info:eu-repo/semantics/acceptedVersio

St(D)reaming Resolution: Crowd-Based Stepped Online Dispute Resolution for Professional Gamers, VTubers & Streamers

This paper proposes and creates a novel method to resolve disputes between content creators, Vtubers, Professional Gamers, and streamers by utilizing a crowd based stepped dispute resolution system upheld and voted on by viewers, shareholders, and the streaming company: Twitch or YouTube. To reach this goal, the proposal will include comparisons to the current dispute resolution system used by Twitch and YouTube; a proposed online dispute resolution system; diagrams of the proposal; key performance indexes (KPI’s); utilization of arbitral analytics with artificial intelligence to create a fair and balanced resolution system; and some predictions on the future of the industry with these changes in mind

SENTIMENT ANALYSIS ON E-SPORTS FOR EDUCATION CURRICULUM USING NAIVE BAYES AND SUPPORT VECTOR MACHINE

The development of e-sports education is not just playing games, but about start making, development, marketing, research and other forms education aimed at training skills and providing knowledge in fostering character. The opinions expressed by the public can take form support, criticism and input. Very large volume of comments need to be analyzed accurately in order separate positive and negative sentiments. This research was conducted to measure opinions or separate positive and negative sentiments towards e-sports education, so that valuable information can be sought from social media. Data used in this study was obtained by crawling on social media Twitter. This study uses a classification algorithm, Naïve Bayes and Support Vector Machine. Comparison two algorithms produces predictions obtained that the Naïve Bayes algorithm with SMOTE gets accuracy value 70.32%, and AUC value 0.954. While Support Vector Machine with SMOTE gets accuracy value 66.92% and AUC value 0.832. From these results can be concluded that Naïve Bayes algorithm has a higher accuracy compared to Support Vector Machine algorithm, it can be seen that the accuracy difference between naïve Bayes and the vector machine support is 3.4%. Naïve Bayes algorithm can thus better predict the achievement of e-sports for students' learning curriculum

Trust beyond reputation: A computational trust model based on stereotypes

Models of computational trust support users in taking decisions. They are commonly used to guide users' judgements in online auction sites; or to determine quality of contributions in Web 2.0 sites. However, most existing systems require historical information about the past behavior of the specific agent being judged. In contrast, in real life, to anticipate and to predict a stranger's actions in absence of the knowledge of such behavioral history, we often use our "instinct"- essentially stereotypes developed from our past interactions with other "similar" persons. In this paper, we propose StereoTrust, a computational trust model inspired by stereotypes as used in real-life. A stereotype contains certain features of agents and an expected outcome of the transaction. When facing a stranger, an agent derives its trust by aggregating stereotypes matching the stranger's profile. Since stereotypes are formed locally, recommendations stem from the trustor's own personal experiences and perspective. Historical behavioral information, when available, can be used to refine the analysis. According to our experiments using Epinions.com dataset, StereoTrust compares favorably with existing trust models that use different kinds of information and more complete historical information

Assessing COVID-19 impact on user opinion towards videogames - Sentiment analysis and structural break detection on steam data

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceAs we live in a world where the videogame industry grows day by day and new media is constantly emerging, user feedback can be widely found online. User reviews are a highly valuable data source when studying player perception of a videogame. They are also apparently volatile to updates released by developers and other external events, which may change user opinion over time. Here we assess whether the COVID-19 pandemic outbreak fell in this category, having or not a noticeable impact on the player view and popularity of videogames. In this research, we build and implement a method to collect active player data and user reviews, identifying the sentiment contained in the expressed opinions. Furthermore, we investigate the existence of structural breaks in the time series we target. For this purpose, we targeted user-reviews and active player data collected of Steam’s twenty most popular Massive Multiplayer Online Role- Playing Games. To collect sentiment polarity values, two Natural Language Processing Python libraries were used, TextBlob and VADER, and structural break detection was put into practice using strucchange R package. The results of this work show us that despite having a great effect on the number of active players, the COVID-19 pandemic did not produce the same impact on Steam user reviews. Nonetheless, we were able to identify one of the platform’s major reviewing related updates as a structural break. We believe this approach can be used for further assessments on public opinion towards a specific product, in the future

Sentiment analysis: the case of twitch chat - Mining user feedback from livestream chats

Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementIn a world where users often share their thoughts and opinions through online communication channels, applications that can tap into these channels as to extract consumer feedback have become increasingly valuable. Traditional marketing research techniques such as interviews or surveys offer results that pale in comparison to sentiment analysis applications that can extract organic feedback from an extremely large selection, with very little resources and in real-time. This thesis focuses on proposing and developing one of these tools that targets livestreams, which have, over the years, seen a massive increase in popularity from both a user-base standpoint as well as brand involvement. We chose the livestreaming platform “Twitch” as the target of research and developed a sentiment analysis model, using rule-based approaches, capable of interpreting user chat messages and identifying whether those messages are negative, positive or neutral. Additionally, an application was developed to better view and analyze the results of the model. By segmenting our results by product reveal, we also exhibit how the application allows for the extraction of various insights about the public’s opinion of that product

Predicting Twitch.tv Donations using Sentiment Analysis

Twitch.tv streamers have a rare opportunity to receive immediate feedback from their audience through a real-time chat log that is rife with sentiment information. Tools that can help a streamer understand how they need to influence their audience can be useful in increasing the donations and subscriptions they earn. Although millions around the world stream on Twitch, only a minuscule fraction of these streamers earn a living streaming alone. This paper aimed to provide muchneeded guidance to enable more streamers to succeed. We used stream logs, known as VODs (video on demand), which can be easily accessed through Twitch’s API or web interface, and parsed these logs for chat and donation data. After normalizing the data, we performed sentiment analysis using a combination of VADER, TextBlob, and Flair algorithms. We found that chat sentiment is a useful indicator for predicting the occurrence of donations. The results have set the foundation future researchers and developers can use to create tools and further our collective understanding of stream viewer sentiment

Gamer speak : a case study of gaming terminology in Spain

La globalització dels videojocs ha obert noves vies d'investigació en el camp de la traducció. Encara que la localització de videojocs és objecte d'estudi, existeixen poques investigacions sobre l'ús real de terminologia lúdica que realitzen els jugadors espanyols. Per tenir un coneixement més profund de "gamer speak", l'argot real usat pels jugadors espanyols, cal donar més atenció acadèmica a la influència que exerceix l'anglès sobre el seu lèxic. Mitjançant un estudi de corpus exploratori, s'extreu la terminologia "gaming" d'una selecció de vídeos "Let's Play" publicats per dos YouTubers espanyols. S'analitza la lexicologia dels termes per revelar els processes neològics i mecanismes de creació de paraules que constitueixen el lèxic compartit per la comunitat de jugadors a Espanya. L'anàlisi de les dades extretes del corpus confirma que els jugadors espanyols depenen de la terminologia anglesa mentre juguen, en manllevar i adaptar paraules estrangeres, i generalment ignoren termes que han sigut localitzats en pro de l'argot col·loquial establert. S'han de realitzar més estudis sobre aquesta discrepància per entendre la mecànica que regeix aquestes preferències.La globalización de los videojuegos ha abierto nuevas vías de investigación en el campo de la traducción. Aunque la localización de videojuegos es objeto de estudio, existen pocas investigaciones sobre el uso real de terminología lúdica que realizan los jugadores españoles. Para tener un conocimiento más profundo de "gamer speak", la jerga real usada por jugadores españoles, se debe prestar más atención académica a la influencia que ejerce el inglés sobre su léxico. Mediante un estudio de corpus exploratorio, se extrae la terminología "gaming" de una selección de vídeos "Let's Play" publicados por dos YouTubers españoles. Se analiza la lexicología de los términos para desvelar los procesos neológicos y mecanismos de creación de palabras que dan lugar al léxico compartido por la comunidad de jugadores de España. El análisis de los datos extraídos del corpus confirma que los jugadores españoles dependen de la terminología inglesa mientras juegan, al tomar prestadas y adaptar palabras extranjeras, y generalmente ignoran términos que han sido localizados en pro del argot coloquial establecido. Se deben realizar más estudios sobre esta discrepancia para entender la mecánica que rige estas preferencias.The globalization of video games has opened new investigation pathways for translation studies. While research is being performed on video game localization, little academic research has focused on the real-life application of gaming terminology by Spanish gamers. In order to bring awareness to "gamer speak", real-world gaming lingo used by Spanish players, the influence of English on their lexicon requires academic attention. Through an exploratory corpus study, gaming terminology is extracted from a selection of "Let's Play" videos posted by two Spanish YouTubers. Lexicology of the terms is analyzed to uncover the neology processes and word creation mechanisms that give rise to the lexis shared by the Spanish gaming community. The analysis of the data extracted from the corpus confirms that Spanish gamers rely heavily on English terminology during gameplay, borrowing and adapting foreign words, and generally ignore officially localized terms in favor of colloquially established jargon. Further investigation must be performed into this discrepancy in order to understand the mechanics behind these preferences