252 research outputs found
A Computational Narrative Analysis of Children-Parent Attachment Relationships
Children narratives implicitly represent their experiences and emotions. The relationships infants establish with their environment will shape their relationships with others and the concept of themselves. In this context, the Attachment Story Completion Task (ASCT) contains a series of unfinished stories to project the self in relation to attachment. Unfinished story procedures present a dilemma which needs to be solved and a codification of the secure, secure/insecure or insecure attachment categories. This paper analyses a story-corpus to explain 3 to 6 year old children-parent attachment relationships. It is a computational approach to exploring attachment representational models in two unfinished story-lines: "The stolen bike" and "The present". The resulting corpora contains 184 stories in one corpus and 170 stories in the other. The Latent Semantic Analysis (LSA) and Linguistic Inquiry and Word Count (LIWC) computational frameworks observe the emotions which children project. As a result, the computational analysis of the children mental representational model, in both corpora, have shown to be comparable to expert judgements in attachment categorization
'Ephemerality’ in game development: opportunitiees and challenges
Ephemeral Computation (Eph-C) is a newly created computation paradigm, the purpose of which is to take advantage of the ephemeral nature (limited lifetime) of computational resources. First we speak of this new paradigm in general terms, then more specifically in terms of videogame development.
We present possible applications and benefits for
the main research fields associated with videogame development. This is a preliminary work which aims to investigate the possibilities of applying ephemeral computation to the products of the videogame industry. Therefore, as a preliminary work, it attempts to serve as the inspiration for other researchers or videogame developers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech
A Survey on Event-based News Narrative Extraction
Narratives are fundamental to our understanding of the world, providing us
with a natural structure for knowledge representation over time. Computational
narrative extraction is a subfield of artificial intelligence that makes heavy
use of information retrieval and natural language processing techniques.
Despite the importance of computational narrative extraction, relatively little
scholarly work exists on synthesizing previous research and strategizing future
research in the area. In particular, this article focuses on extracting news
narratives from an event-centric perspective. Extracting narratives from news
data has multiple applications in understanding the evolving information
landscape. This survey presents an extensive study of research in the area of
event-based news narrative extraction. In particular, we screened over 900
articles that yielded 54 relevant articles. These articles are synthesized and
organized by representation model, extraction criteria, and evaluation
approaches. Based on the reviewed studies, we identify recent trends, open
challenges, and potential research lines.Comment: 37 pages, 3 figures, to be published in the journal ACM CSU
Conversational Exploratory Search via Interactive Storytelling
Conversational interfaces are likely to become more efficient, intuitive and
engaging way for human-computer interaction than today's text or touch-based
interfaces. Current research efforts concerning conversational interfaces focus
primarily on question answering functionality, thereby neglecting support for
search activities beyond targeted information lookup. Users engage in
exploratory search when they are unfamiliar with the domain of their goal,
unsure about the ways to achieve their goals, or unsure about their goals in
the first place. Exploratory search is often supported by approaches from
information visualization. However, such approaches cannot be directly
translated to the setting of conversational search.
In this paper we investigate the affordances of interactive storytelling as a
tool to enable exploratory search within the framework of a conversational
interface. Interactive storytelling provides a way to navigate a document
collection in the pace and order a user prefers. In our vision, interactive
storytelling is to be coupled with a dialogue-based system that provides verbal
explanations and responsive design. We discuss challenges and sketch the
research agenda required to put this vision into life.Comment: Accepted at ICTIR'17 Workshop on Search-Oriented Conversational AI
(SCAI 2017
Exploring narrative presentation for large multimodal lifelog collections through card sorting
Using lifelogging tools, personal digital artifacts are collected continuously and passively throughout each day. The wealth of information such an archive contains on our life history provides novel opportunities for the creation of digital life narratives. However, the complexity, volume and multimodal nature of such collections create barriers to achieving this. Nine participants engaged in a card-sorting activity designed to explore practices of content reduction and presentation for narrative composition. We found the visual modalities to be most fluent in communicating experience with other modalities serving to support them and that the users employed the salient themes of the story to organise, arrange and facilitate filtering of the content
Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare
Risk assessment algorithms are being adopted by public sector agencies to
make high-stakes decisions about human lives. Algorithms model "risk" based on
individual client characteristics to identify clients most in need. However,
this understanding of risk is primarily based on easily quantifiable risk
factors that present an incomplete and biased perspective of clients. We
conducted a computational narrative analysis of child-welfare casenotes and
draw attention to deeper systemic risk factors that are hard to quantify but
directly impact families and street-level decision-making. We found that beyond
individual risk factors, the system itself poses a significant amount of risk
where parents are over-surveilled by caseworkers and lack agency in
decision-making processes. We also problematize the notion of risk as a static
construct by highlighting the temporality and mediating effects of different
risk, protective, systemic, and procedural factors. Finally, we draw caution
against using casenotes in NLP-based systems by unpacking their limitations and
biases embedded within them
Ontological Approaches to Modelling Narrative
We outline a simple taxonomy of approaches to modelling narrative, explain how these might be realised ontologically, and describe our continuing work to apply these techniques to the problem of Memories for Life
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