Aboutness em Análise Documental de textos literários infanto-juvenis: perspectivas para o aprimoramento da representação de conteúdo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The use of narrative text for injury surveillance research : a systematic review

Objective: To summarise the extent to which narrative text fields in administrative health data are used to gather information about the event resulting in presentation to a health care provider for treatment of an injury, and to highlight best practise approaches to conducting narrative text interrogation for injury surveillance purposes.----- Design: Systematic review----- Data sources: Electronic databases searched included CINAHL, Google Scholar, Medline, Proquest, PubMed and PubMed Central.. Snowballing strategies were employed by searching the bibliographies of retrieved references to identify relevant associated articles.----- Selection criteria: Papers were selected if the study used a health-related database and if the study objectives were to a) use text field to identify injury cases or use text fields to extract additional information on injury circumstances not available from coded data or b) use text fields to assess accuracy of coded data fields for injury-related cases or c) describe methods/approaches for extracting injury information from text fields.----- Methods: The papers identified through the search were independently screened by two authors for inclusion, resulting in 41 papers selected for review. Due to heterogeneity between studies metaanalysis was not performed.----- Results: The majority of papers reviewed focused on describing injury epidemiology trends using coded data and text fields to supplement coded data (28 papers), with these studies demonstrating the value of text data for providing more specific information beyond what had been coded to enable case selection or provide circumstantial information. Caveats were expressed in terms of the consistency and completeness of recording of text information resulting in underestimates when using these data. Four coding validation papers were reviewed with these studies showing the utility of text data for validating and checking the accuracy of coded data. Seven studies (9 papers) described methods for interrogating injury text fields for systematic extraction of information, with a combination of manual and semi-automated methods used to refine and develop algorithms for extraction and classification of coded data from text. Quality assurance approaches to assessing the robustness of the methods for extracting text data was only discussed in 8 of the epidemiology papers, and 1 of the coding validation papers. All of the text interrogation methodology papers described systematic approaches to ensuring the quality of the approach.----- Conclusions: Manual review and coding approaches, text search methods, and statistical tools have been utilised to extract data from narrative text and translate it into useable, detailed injury event information. These techniques can and have been applied to administrative datasets to identify specific injury types and add value to previously coded injury datasets. Only a few studies thoroughly described the methods which were used for text mining and less than half of the studies which were reviewed used/described quality assurance methods for ensuring the robustness of the approach. New techniques utilising semi-automated computerised approaches and Bayesian/clustering statistical methods offer the potential to further develop and standardise the analysis of narrative text for injury surveillance.

Injury narrative text classification : a preliminary study

Description of a patient's injuries is recorded in narrative text form by hospital emergency departments. For statistical reporting, this text data needs to be mapped to pre-defined codes. Existing research in this field uses the Naïve Bayes probabilistic method to build classifiers for mapping. In this paper, we focus on providing guidance on the selection of a classification method. We build a number of classifiers belonging to different classification families such as decision tree, probabilistic, neural networks, and instance-based, ensemble-based and kernel-based linear classifiers. An extensive pre-processing is carried out to ensure the quality of data and, in hence, the quality classification outcome. The records with a null entry in injury description are removed. The misspelling correction process is carried out by finding and replacing the misspelt word with a soundlike word. Meaningful phrases have been identified and kept, instead of removing the part of phrase as a stop word. The abbreviations appearing in many forms of entry are manually identified and only one form of abbreviations is used. Clustering is utilised to discriminate between non-frequent and frequent terms. This process reduced the number of text features dramatically from about 28,000 to 5000. The medical narrative text injury dataset, under consideration, is composed of many short documents. The data can be characterized as high-dimensional and sparse, i.e., few features are irrelevant but features are correlated with one another. Therefore, Matrix factorization techniques such as Singular Value Decomposition (SVD) and Non Negative Matrix Factorization (NNMF) have been used to map the processed feature space to a lower-dimensional feature space. Classifiers with these reduced feature space have been built. In experiments, a set of tests are conducted to reflect which classification method is best for the medical text classification. The Non Negative Matrix Factorization with Support Vector Machine method can achieve 93% precision which is higher than all the tested traditional classifiers. We also found that TF/IDF weighting which works well for long text classification is inferior to binary weighting in short document classification. Another finding is that the Top-n terms should be removed in consultation with medical experts, as it affects the classification performance.

Injury narrative text classification using factorization model

Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently reduce the tedious manual classification process. Existing works focus on using Naive Bayes which does not always offer the best performance. This paper proposes the Matrix Factorization approaches along with a learning enhancement process for this task. The results are compared with the performance of various other classification approaches. The impact on the classification results from the parameters setting during the classification of a medical text dataset is discussed. With the selection of right dimension k, Non Negative Matrix Factorization-model method achieves 10 CV accuracy of 0.93.

On the Epistemology of Narrative Theory: Narratology and Other Theories of Fictional Narrative

In this article, I propose to analyze narrative theory from an epistemological standpoint. To do so, I will draw upon both Genettian narratology and what I would call, following Shigeyuki Kuroda, “non-communicational” theories of fictional narrative. In spite of their very unequal popularity, I consider these theories as objective, or, in other words, as debatable and ripe for rational analyses; one can choose between them. The article is made up of three parts. The first part concerns the object of narrative theory, or the narrative as a constructed object, both in narratology (where narrative is likened to a narrative discourse) and in non-communicational narrative theories (where fictional narrative and discourse are mutually exclusive categories). The second part takes up the question of how the claims of these theories do or do not lend themselves to falsification. In particular, Gérard Genette’s claim that “every narrative is, explicitly or not, ‘in the first person’”, will be considered, through the lens of Ann Banfield’s theory of free indirect style. In the third part the reductionism of narrative theory will be dealt with. This leads to a reflection on the role of narrative theory in the analysis of fictional narratives.

A viagem de um leitor: uma investigação semiótica sobre o processo de leitura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Who speaks up for Inés Fonseca? Representing violence against vulnerable subjects and the ethics of care in fictional narrative about Alzheimer’s disease:Ahora tocad música de baile (2004) by Andrés Barba

This paper studies the Spanish fictional novel by Andrés Barba, Ahora tocad música de baile (2004), one of the first cultural texts dealing entirely with Alzheimer’s disease (AD) to appear in Spain. It argues that the significance of Barba’s fictional novel rests on two important issues: the ethics of representation of violence against vulnerable subjects and the ethics of care. The paper analyses how these two issues allow Barba to create a story in which the verbal and physical abuse to which the person living with Alzheimer’s disease is subjected places the reader, on the one hand, as voyeur/witness of the abuse; and, on the other, as interpreter, and ultimately judge, of the fine line that separates euthanasia, assisted suicide, and murder. The open ending of the novel defers all ethical and moral judgment to the reader. It examines how the novel offers a monolithic perspective about AD, in which care is presented as a burden. In fact, this study shows that the novel’s multi-layered structure and polyphonic nature places the emphasis on stigmas, stereotypes and negative metaphors around AD, as found in contemporary social discourses.

THE ARGUMENTATIVE AND POLYPHONIC FUNCTION OF THE NARRATIVE TEXT

In this paper, aims to verify how to happen the argumentative and polyphonic function of the narrative text, from the analysis of the tale A moça tecelã (The weaver girl) from Marina Colasanti. Therefore, the article is based in presuppositions of the Semantic Theory of the Blocks and in concepts taken from the Enunciation Polyphonic Theory, proposed by Ducrot (1984a, 1988). We defend the hypotheses: a) the narrative of the tale A moça tecelã is determined by meanings of “time”, while element responsible to bring and take away events; b) the narrative texts are crossed by the argumentation constituent of the viewpoint expressed by the enunciator, put in scene by the speaker; c) the argumentative function of the tale mobilizes two discourses about marriage. As a result, it was noted that in the narrative texts are found argumentative discourses, that were formalized in utterances produced from the semantic analysis of the tale A moça tecelã and by which function in this tale two concepts of time e two discourses about marriage.  

Análise documental em textos narrativos de ficção: subsídios para o processo de análise

Pós-graduação em Ciência da Informação - FFC

Cohesion in text differentiation : a study of English and Arabic

This thesis sets out to investigate the role of cohesion in the organisation and processing of three text types in English and Arabic. In other words, it attempts to shed some light on the descriptive and explanatory power of cohesion in different text typologies. To this effect, three text types, namely, literary fictional narrative, newspaper editorial and science were analysed to ascertain the intra- and inter-sentential trends in textual cohesion characteristic of each text type in each language. In addition, two small scale experiments which aimed at exploring the facilitatory effect of one cohesive device (i.e. lexical repetition) on the comprehension of three English text types by Arab learners were carried out. The first experiment examined this effect in an English science text; the second covered three English text types, i.e. fictional narrative, culturally-oriented and science. Some interesting and significant results have emerged from the textual analysis and the pilot studies. Most importantly, each text type tends to utilize the cohesive trends that are compatible with its readership, reader knowledge, reading style and pedagogical purpose. Whereas fictional narratives largely cohere through pronominal co-reference, editorials and science texts derive much cohesion from lexical repetition. As for cross-language differences English opts for economy in the use of cohesive devices, while Arabic largely coheres through the redundant effect created by the high frequency of most of those devices. Thus, cohesion is proved to be a variable rather than a homogeneous phenomenon which is dictated by text type among other factors. The results of the experiments suggest that lexical repetition does facilitate the comprehension of English texts by Arab learners. Fictional narratives are found to be easier to process and understand than expository texts. Consequently, cohesion can assist in the processing of text as it can in its creation.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

ME and Julie:a study in narrative of illness experience and therapy in a Myalgic Encephalomyelitis sufferer

This article uses what Atkinson and Walmsley (1997) refer to as an ‘autobiographical account’ to explore the themes and relationships between narrative, illness experience and therapy in a Myalgic Encephalomyelitis (ME) sufferer. Julie is a chronic ME sufferer, having lived with ME for the past 12 years. Her life-story over those years, as she presents it, casts our attention to the intrinsically personal nature of her ‘illness experience’ and to her distinctively artistic therapeutic responses to her condition. Julie’s autobiographical narrative reveals how ME has penetrated both her body and her sense of self, her limbs as well as her dreams; as though it were a parasite feeding off her fight to regain health. In terms of narrative, Julie’s ME illness progresses from past to present, but never to the future which lies beyond contemplation. Despite this denial of the future, Julie does think of ME as a liminal phase which is to be coped through. As both spatial object and temporal event, Julie conceptualises her ME variously, dealing with it on a day-to-day basis, increasingly turning to landscape painting as a form of escapism which parallels her former physical outward bound activities. This personal therapy, so this article concludes, constitutes both narrative performance and narrative text (as canvas), both of which can only cautiously be independently interpreted by the (inter)viewer.

O (in)dizível em Uma aventura secreta do Marquês de Bradomín de Teresa Veiga

A dissertação baseia-se numa leitura do conto “Uma aventura secreta do marquês de Bradomín”. Este texto narrativo destaca questões relacionadas com a ficção contemporânea portuguesa, como a construção da personagem com estatuto de protagonista, oscilando entre ser real e ser ficcional, a autoria feminina, a importância do dizer e do silêncio. A personagem feminina apresenta a sua história partilhada com o marquês de Bradomín e os sentidos mudam em consonância com as condições temporal e discursiva; a simbologia torna-se um acto de ideologia e de interpretação, uma vez que a expressividade humana está para além das palavras, produzindo silêncios enquanto se discursa. A personagem escreve por palavras que ocultam outras, que são apenas aludidas e, como a narradora recorre à memória, o seu texto discursivo pode apresentar-se de forma lacunar, com a desculpa do esquecimento. Neste caso, os sentidos podem ser sempre outros e o (in)dizível persiste.

Mitificación y oralidad en el otoño del patriarca de Gabriel García Márquez

El actual documento presenta los resultados de una investigación que vengo desarrollando hace algunos años sobre El Otoño del Patriarca. Esta investigación sufrió una importante variación en torno a la reflexión sobre los propósitos de la lectura filosófica de un texto literario, y ha sido consecuencia de, por un lado, un desplazamiento en la determinación de las relaciones entre las dimensiones del lenguaje, el poder, el tiempo y el espacio abiertos por la narración, y por otro, de una diferencia de concepción sobre la formación discursiva de estas relaciones en El Otoño del Patriarca como obra narrativa, oral y poética.