Computing and Information Systems - Research Publications
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ItemDeath and the Internet: Consumer issues for planning and managing digital legacies (2nd edition)(Australian Communications Consumer Action Network, 2017-12-01)
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ItemEsports Spectatorship in Australia(Networked Society Institute, 2018)Esports – the organised, professional and spectated play of competitive digital games – has evolved into a massive global industry in the past decade. Boasting significant market value and broad global audience reach, esports is driven by modern highspeed internet infrastructure and live-streaming platforms like Twitch.tv. However, esports has yet to take hold as an industry in Australia, largely due to geographical isolation from major esports regions compounded by Australia’s traditionally lacklustre network infrastructure. Although the esports industry relies on various revenue streams, sponsorship and advertising deals provide the industry’s main source of funding. Teams, tournaments and esports organisations of various sizes are sponsored by major international companies like Intel, Samsung and Mercedes-Benz. This is unsurprising considering the global reach of esports. According to the ‘market intelligence’ firm Newzoo (2017), the esports audience in 2017 is estimated to be 385 million, with rough half of those being ‘enthusiasts’ and the other half ‘occasional viewers’. Furthermore, they estimate that the esports industry generated roughly US $696 million in revenue through ticket sales, media rights, game publisher fees, advertising and merchandise, sponsorship, media rights, in-game microtransactions, and betting in 2017. Newzoo estimates this amount to grow to US $906 million in 2018. Revenue growth for the esports industry has been significant, with current estimates pointing to a year-over-year growth of 41% in 2017, of which US$517 million is in advertising, sponsorship, and media rights (Newzoo 2017). While global industry reports are optimistic about the future of esports, the Australian esports scene is limited in comparison to overseas markets. In this report, we start by approximating the size of the esports market in Australia by comparing publicly available statistics and collecting a list of major global and Australian esports events. Secondly, we provide an overview of key Australian esports titles, explaining how they’re played as esports and their place within the Australian esports landscape. Thirdly, we explore the practice of spectating esports and discuss motivations behind esports spectatorship. We then present a preliminary study consisting of 18 semi-structured interviews with esports spectators regarding their engagement with and consumption of esports content. From our findings, we identify and detail three salient categories of non-exclusive esports spectator types: players, fans and recruits. We conclude with a summary of key changes in the Australia esports landscape during 2018 and important upcoming developments.
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ItemTimestamp Repair for Business Process Event Logs( 2018-04-05)This paper contributes an approach for automatically correcting timestamp errors in business process execution logs. These errors are quite common in practice due to the logging granularity or the performance load of the logging system. Analyzing logs that have not been properly screened for such problems is likely to lead to wrong or misleading process insights. The proposed approach revolves around two techniques: one to reorder events with erroneous timestamps, the other to assign an estimated timestamp to each such event. The approach has been implemented in a software tool and extensively evaluated in different settings, using both synthetic and real-life logs. The experiments show that the approach significantly reduces the amount of incorrect timestamps, while the reordering of events scales well to large and complex datasets. The evaluation is complemented by a case study in the meat & livestock domain showing the usefulness of the approach in practice.
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ItemBehavioural Quotients for Precision and Recall in Process Mining( 2018)The comparison of the languages of software systems, i.e., their behaviours in terms of specified executions, is a prerequisite for many applications, reaching from system validation through management of a system's evolution to conformance checking of observed and expected behaviour. If two systems are not language-equivalent, the quantification of behavioural differences enables conclusions on the extent of deviation. Such quantifications are commonly done in a relative manner: A quotient is defined over some measure of two languages, which have potentially been derived via algebraic operations. However, there exists no systematic approach for defining quotients and it is unclear which measures enable meaningful comparisons of systems having infinite behaviours. This paper introduces a framework for defining language quotients. We instantiate the framework with cardinality-based and entropy-based measures to handle finite and infinite behaviours, and prove important properties of the quotients. We demonstrate application of quotients in the field of process mining to capture precision and recall between a log of recorded system executions and a model of expected system executions. An experimental evaluation of the quotients using our open-source implementation demonstrates their feasibility and indicates that the quotients enable a monotonic assessment, unlike state-of-the-art measures in process mining.