The StorySpinner Sculptural Reader

This demo is of a hypertext reading system called StorySpinner. It follows the sculptural hypertext methodology and has been used as a test bed for experimenting with the authoring of narrative flow in automatically generated stories. Readers are able to select and read one of two available stories. Reading a story involves selecting tarot cards which are mapped to chunks of story text based on possible interpretations of the cards and information concerning current story state

StorySpinner: Controlling Narrative Pace in Hyperfiction

This paper describes the StorySpinner system, a sculptural hypertext reader used as a test bed for experimenting with the authoring of narrative flow in automatically generated stories. An overview of the system is presented along with discussion and conclusions arising from initial user trials

Patterns of implicit and non-follower retweet propagation: investigating the role of applications and hashtags

Existing literature on retweets seems to focus mainly on retweets created using explicit, formal retweeting mechanisms, such as Twitter's own native retweet function, and the prefixing of the terms 'RT' or 'via' in front of copied tweets. However, retweets can also be made using implicit, informal mechanisms. These include tweet replies and other mechanisms, which use neither the native nor RT/via mechanisms, but their content and timelines suggest the likelihood of being a retweet. Moreover, retweets can also occur with or without a defined follower/following network path between a tweet originator and a retweeter. This paper presents an initial taxonomy of propagation based on seven different ways a tweet may spread: native, native non-follower, RT/Via, RT/Via non-follower, replies, non-follower replies and other implicit 'retweets'. An experiment has examined this new model, by investigating where tweets containing URLs from the domains of online petitions, charity fundraisers, news portals, and YouTube videos can be classified into the seven different categories. When including other implicit 'retweets', more than 50% of all the retweets found across all four domains were classified as implicit retweets, while more than 79% of all retweets were made by non-followers. More work needs to be done on the composition of other implicit 'retweets'. Initial investigations found hashtags in 99-100% of these tweets, suggesting that retweeting using conventional mechanisms may not be the main method that URLs get propagated across microblogs

Towards modelling dialectic and eristic argumentation on the social web

Modelling arguments on the social web is a key challenge for those studying computational argumentation. This is because formal models of argumentation tend to assume dialectic and logical argument, whereas argumentation on the social web is highly eristic. In this paper we explore this gap by bringing together the Argument Interchange Format (AIF) and the Semantic Interlinked Online Communities (SIOC) project, and modelling a sample of social web arguments. This allows us to explore which eristic effects cannot be modelled, and also to see which features of the social web are missing.We show that even in our small sample, from YouTube, Twitter and Facebook, eristic effects (such as playing to the audience) were missing from the final model, and that key social features (such as likes and dislikes) were also not represented. This suggests that both eristic and social extensions need to be made to our models of argumentation in order to deal effectively with the social we

Skim reading: an adaptive strategy for reading on the web

It has been suggested that readers spend a great deal of time skim reading on the Web and that if readers skim read they reduce their comprehension of what they have read. There have been a number of studies exploring skim reading, but relatively little exists on the skim reading of hypertext and Webpages. In the experiment documented here, we utilised eye tracking methodology to explore how readers skim read hypertext and how hyperlinks affect reading behaviour. The results show that the readers read faster when they were skim reading and comprehension was reduced. However, the presence of hyperlinks seemed to assist the readers in picking out important information when skim reading. We suggest that readers engage in an adaptive information foraging strategy where they attempt to minimise comprehension loss while maintaining a high reading speed. Readers use hyperlinks as markers to suggest important information and use them to read through the text in an efficient and effective way. This suggests that skim reading may not be as damaging to comprehension when reading hypertext, but it does mean that the words we choose to hyperlink become very important to comprehension for those skim reading text on the Web

On measuring the impact of hyperlinks on reading

We increasingly spend a vast amount of time on the Web and much of that time is spent reading. One of the main differences between reading non-Web based text and reading on the Web is the presence of hyperlinks within the text, linking various related Web content and Web pages together. Some researchers and commentators have claimed that hyperlinks hinder reading because they are a distraction that may have a negative effect on the reader’s ability to process the text. However, very few controlled experiments have been conducted to verify these claims.In the experiments documented here we utilise eye tracking as a new methodology for examining how we read hyperlinked text. An eye tracker was used to observe participant’s behaviour while reading. The results showed that hyperlinked text did not generally have a negative impact upon reading behaviour. However, participants did show a tendency to re-read sentences that contained hyperlinked uncommon (low frequency) words. This suggests that hyperlinks highlight important information to the reader and the hyperlinks add additional content which for more difficult concepts, invites rereading of the preceding text

An On-the-fly Provenance Tracking Mechanism for Stream Processing Systems

Applications that operate over streaming data withhigh-volume and real-time processing requirements are becomingincreasingly important. These applications process streamingdata in real-time and deliver instantaneous responses to supportprecise and on-time decisions. In such systems, traceability -the ability to verify and investigate the source of a particularoutput - in real-time is extremely important. This ability allowsraw streaming data to be checked and processing steps to beverified and validated in timely manner. Therefore, it is crucialthat stream systems have a mechanism for dynamically trackingprovenance - the process that produced result data - at executiontime, which we refer to as on-the-fly stream provenance tracking.In this paper, we propose a novel on-the-fly provenance trackingmechanism that enables provenance queries to be performeddynamically without requiring provenance assertions to be storedpersistently. We demonstrate how our provenance mechanismworks by means of an on-the-fly provenance tracking algorithm.The experimental evaluation shows that our provenance solutiondoes not have a significant effect on the normal processing ofstream systems given a 7% overhead. Moreover, our provenancesolution offers low-latency processing (0.3 ms per additionalcomponent) with reasonable memory consumption.<br/

Visualisation of Hypermedia Systems: An Open Approach

Hypermedia systems are designed to allow links, or connections, to be made between different media objects. Key issues tackled in early hypermedia systems included developing tools to help guide users through the material and tools to help authors maintain the material that they create. The open approach to hypermedia emerged, where links were separated from the content of documents, allowing a more modular approach to hypermedia services. The ease of integration of tools in these open systems promoted the creation of many different types of navigational aids, designed to help users of the systems to access and maintain the information contained within them. The openness and modular nature of such systems creates its own problems however. Users will often have to interact with a number of disparate interfaces to manipulate the navigational information. A new approach is presented which provides an open framework for these interfaces, allowing for a co-ordinated strategy and the modular addition of tools to help manage the screen interface and reduce the complexity of the interaction for users. A second approach to the problem is to provide the different hypermedia information within a unifying visualisation. A novel framework is presented which allows more open access to the underlying navigational information of hypermedia systems. Visualisation tools can be connected to this framework in a modular fashion to provide flexible visualisations of the underlying information. By generating a number of different visualisations, the openness and flexibility of the visualisation framework approach is demonstrated

Exposing potential narrative structure through user choice

The reading of a hypertext fiction could simply be viewed as the reordering of events, reviewing and accessing fragments of a story that has already taken place. A different reader experience would come from different orderings and the effects that these might produce. This doesn’t have to be the case however. The fragments of a fiction also can represent possibilities that have yet to occur. This is independent of the over-arching narrative of the piece. At points in the fiction the reader is presented with choices. Do I follow this link or do I choose a different path? Here, the narrative structure of the piece is leaking through the text and not just the read structure but potential future structures. These choices must be presented to the reader by the author. This paper will examine some of the consequences of exposing the visibilities of these narrative structures, using the presentation of choices in hypertext fiction as an exemplar

Using hidden Markov models for iterative non-intrusive appliance monitoring

Non-intrusive appliance load monitoring is the process of breaking down a household’s total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances are iteratively separated from the aggregate load. Our approach does not require training data to be collected by sub-metering individual appliances. Instead, prior models of general appliance types are tuned to specific appliance instances using only signatures extracted from the aggregate load. The tuned appliance models are used to estimate each appliance’s load, which is subsequently subtracted from the aggregate load. We evaluate our approach using the REDD data set, and show that it can disaggregate 35% of a typical household’s total energy consumption to an accuracy of 83% by only disaggregating three of its highest energy consuming appliances