The Hardcore Scorecard: Defining, Quantifying and Understanding “Hardcore” Video Game Culture

ABSTRACT The goal of the current study is to further conceptualize and define the term “hardcore” as it relates to video game culture. Past research indicates that members of cultural subdivisions favor their own group versus others due to perceived commonalities (Durkheim, 1915; Tajfel, 1970). In gaming culture, the subdivisions of “hardcore” and “casual” games/gamers have become especially salient in recent years. However, the definition of what constitutes “hardcore” and “casual” is inconsistent (Adams, 2000; Alexandre, 2012; Jacobs & Ip, 2003; Juul, 2010; Kim, 2001; Kuittinen, Kultima, Niemelä & Paavilainen, 2007; Wallace & Robbins, 2006). Therefore, it is beneficial to better understand these terms considering the implications: less audience infighting, more accurately tailored game design/marketing, and less ambiguous/sensationalist gaming journalism/media. A sample of 109 undergraduate students from a large university (19,000 undergraduates) in an upstate New York city (metropolitan population of 1.1 million) completed an online survey, reporting their perceptions of hardcore gaming. Values were then attributed to certain video game criteria based on the survey results and applied to popular games. The sum of these values produced a hardcore index for the “scorecard.” To assess the scorecard’s validity, correlations were run between our final values and an independently collected hardcore percentage publicly available on the Wii’s Nintendo Channel (327,818.45 average respondents per game). Results suggest hardcore gaming is perceived as a harsh subculture consisting of long play times, challenging play, anti-social behavior, and content not suitable for children. The index produced by the resulting “hardcore scorecard” was significantly correlated (r = .765, p \u3c .01) with the independently collected data on the Nintendo Channel. Thus, the current research provides tools the gaming industry (users, developers, journalists) can use to their advantage by better understanding and defining the term “hardcore,” as well as a valuable blueprint for future research to continue refining and improving

Information Sharing During the University of Texas at Austin Active Shooter/Suicide Event

Emergency response systems can be improved by investigating the motives and manner in which people share information during an active shooter crisis. This article analyzed survey data collected from undergraduate participants at The University of Texas at Austin who were enrolled during the fall of 2010 when an active shooter event occurred on campus. Our findings indicated that distance from a threat predicts an individual’s perception of message credibility. Additional findings suggested innovativeness is a strong driving factor in individuals’ reliance on social and personal media to contact others who need safety updates. Finally, perceptions of mortality and experience to negative media portrayals were positively related to active information sharing during this event. Limitations and suggestions for future research are offered

Image attributes and diffusion via twitter: The Case of #guncontrol

We report on a study exploring how Twitter user attributes and the characteristics of the images they share online influence the diffusion of those images. Two-hundred and ninety unique images were collected from Twitter in October 2013 associated with the gun control hash tag [guncontrol]. A coding protocol was developed and images classified based on frame (attribute, goal, or risk), appeal (e.g. Fear, humor), and valence (positive or negative). Results indicate that shared images with attribute frames, fear and humor appeals, and positive valence are retweeted more often. Also retweeted more frequently are messages from users with larger networks and whose tweets contain hash tags. Results also show a significant negative relationship between the time since the last major shooting event in the United States and the likelihood that messages with images are retweeted. These results are discussed in the context of evolving mass media systems and online social networks