Confronting a Paradox: A New Perspective of the Impact of Uncertainty in Suspense.

Suspense is a key narrative issue in terms of emotional gratifications. Reactions in response to this type of entertainment are positively related to enjoyment, having a significant impact on the audience's immersion and suspension of disbelief. Related to computational modeling of this feature, some automatic storytelling systems include limited implementations of suspense management system in their core. In this way, the interest of this subject in the area of creativity has resorted to different definitions from fields as narratology and the film industry, as much as several proposals of its constituent features. Among their characteristics, uncertainty is one of the most discussed in terms of impact and need: while many authors affirm that uncertainty is essential to evoke suspense, others limit or reject its influence. Furthermore, the paradox of suspense reflects the problem of including uncertainty as a component required in suspense creation systems. Due to this need to contrast the effects of the uncertainty in order to compute a general model for automatic storytelling systems, we conducted an experiment measuring suspense experienced by a group of subjects that read a story. While a group of them were told the ending of the story in advance, the members of the other group experimented the same story in chronological order. Both the subjects' reported suspense and their physiological responses are gathered and analyzed. Results provide evidence to conclude that uncertainty affects the emotional response of readers, but independently and in a different form than suspense does. It will help to propose a model in which uncertainty is processed separately as management of the amount of knowledge about the outcome available to the spectator, which acts as a control signal to modulate the input features, but not directly in suspense computing.

Computational Drafting of Plot Structures for Russian Folk Tales.

The plots of stories are known to follow general patterns in terms of their overall structure. This was the basic tenet of structuralist approaches to narratology. Vladimir Propp proposed a procedure for the generation of new tales based on his semi-formal description of the structure of Russian folk tales. This is one of the first existing instances of a creative process described procedurally. The present paper revisits Propp's morphology to build a system that generates instances of Russian folk tales. Propp's view of the folk tale as a rigid sequence of character functions is employed as a plot driver, and some issues that Propp declared relevant but did not explore in detail-such as long-range dependencies between functions or the importance of endings-are given computational shape in the context of a broader architecture that captures all the aspects discussed by Propp. A set of simple evaluation metrics for the resulting outputs is defined inspired on Propp's formalism. The potential of the resulting system for providing a creative story generation system is discussed, and possible lines of future work are discussed.

A semantic graph-based approach to biomedical summarisation.

OBJECTIVE: Access to the vast body of research literature that is available in biomedicine and related fields may be improved by automatic summarisation. This paper presents a method for summarising biomedical scientific literature that takes into consideration the characteristics of the domain and the type of documents. METHODS: To address the problem of identifying salient sentences in biomedical texts, concepts and relations derived from the Unified Medical Language System (UMLS) are arranged to construct a semantic graph that represents the document. A degree-based clustering algorithm is then used to identify different themes or topics within the text. Different heuristics for sentence selection, intended to generate different types of summaries, are tested. A real document case is drawn up to illustrate how the method works. RESULTS: A large-scale evaluation is performed using the recall-oriented understudy for gisting-evaluation (ROUGE) metrics. The results are compared with those achieved by three well-known summarisers (two research prototypes and a commercial application) and two baselines. Our method significantly outperforms all summarisers and baselines. The best of our heuristics achieves an improvement in performance of almost 7.7 percentage units in the ROUGE-1 score over the LexRank summariser (0.7862 versus 0.7302). A qualitative analysis of the summaries also shows that our method succeeds in identifying sentences that cover the main topic of the document and also considers other secondary or "satellite" information that might be relevant to the user. CONCLUSION: The method proposed is proved to be an efficient approach to biomedical literature summarisation, which confirms that the use of concepts rather than terms can be very useful in automatic summarisation, especially when dealing with highly specialised domains.

Integration of Linguistic Markup into Semantic Models of Folk Narratives: The Fairy Tale Use Case.

Propp's influential structural analysis of fairy tales created a powerful schema for representing storylines in terms of character functions, which is straightforward to exploit in computational semantic analysis and procedural generation of stories of this genre. We tackle two resources that draw on the Proppian model - one formalizes it as a semantic markup scheme and the other as an ontology - both lacking linguistic phenomena explicitly represented in them. The need for integrating linguistic information into structured semantic resources is motivated by the emergence of suitable standards that facilitate this, and the benefits such joint representation would create for transdisciplinary research across Digital Humanities, Computational Linguistics, and Artificial Intelligence.