Genre analysis: English in academic and research settings / John M. Swales
01 Jan 1991-Vol. 1991, Iss: 1991, pp 1-99
About: The article was published on 1991-01-01 and is currently open access. It has received 5640 citations till now.
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TL;DR: Cette thematique apparait en outre essentielle pour la linguistique appliquee, tant pour the didactique des langues (aide a la redaction en langue maternelle, didactsique du Francais Langue Etrangere pour l’insertion des etudiants etrangers) que pour le Traitement Automatique du Langage dansl’acces a l”information scientifique
Abstract: Dans les etudes linguistiques sur les ecrits scientifiques, le lexique non terminologique est paradoxalement peu etudie. Les travaux recents portent en effet bien plus frequemment sur les aspects enonciatifs ou rhetoriques (Flottum & al. 2006 ; Hyland 1998 ; Poudat 2005 ; Rinck 2006 ; Rinck & al. 2007 ; Grossmann & Wirth 2007) ou sur les differences disciplinaires (Flottum 2007 ; Hyland & Bondi 2006) que sur les aspects lexicaux a proprement parler. Le lexique a surtout ete aborde dans les travaux sur le FOS (Francais sur Objectifs Specifiques) ou dans les travaux anglo-saxons a travers l’English for Academic Purposes (par exemple Coxhead 2000 ou Hyland 2005) dans la perspective de l’enseignement des langues. Pour le francais, les recherches approfondies restent assez anciennes – hormis la these recente de Pecman (2004) – et les travaux pionniers de Phal (1971), qui demeurent la reference, meritent d’etre actualises. Meme si l’entree lexicale parait parfois difficile a circonscrire – comment definir et delimiter exactement ce lexique propre aux ecrits scientifiques ? −, elle nous semble tout a fait centrale pour une reflexion a la fois epistemologique et linguistique sur les differents types d’ecrits scientifiques, que l’on observe la variable disciplinaire ou que l’on cherche a mettre en evidence les divergences entre les genres d’ecrits scientifiques (articles, theses, rapports, manuels). Cette thematique apparait en outre essentielle pour la
linguistique appliquee, tant pour la didactique des langues (aide a la redaction en langue maternelle, didactique du Francais Langue Etrangere pour l’insertion des etudiants etrangers) que pour le Traitement Automatique du Langage dans l’acces a l’information scientifique ou des besoins importants apparaissent.
36 citations
15 Jun 2009
TL;DR: An automated approach to classify sentences of scholarly work with respect to their rhetorical function is presented, which is robust to noise and can process raw text.
Abstract: We present an automated approach to classify sentences of scholarly work with respect to their rhetorical function. While previous work that achieves this task of argumentative zoning requires richly annotated input, our approach is robust to noise and can process raw text. Even in cases where the input has noise (as it is obtained from optical character recognition or text extraction from PDF files), our robust classifier is largely accurate. We perform an in-depth study of our system both with clean and noisy inputs. We also give preliminary results from in situ acceptability testing when the classifier is embedded within a digital library reading environment.
36 citations
TL;DR: A multistage GN algorithm and a ranking method, which exploit information in different parts of a paper, which is able to improve system performance (AUC) by 1.719 percent compared to a one-stage GN algorithm.
Abstract: The interactor normalization task (INT) is to identify genes that play the interactor role in protein-protein interactions (PPIs), to map these genes to unique IDs, and to rank them according to their normalized confidence. INT has two subtasks: gene normalization (GN) and interactor ranking. The main difficulties of INT GN are identifying genes across species and using full papers instead of abstracts. To tackle these problems, we developed a multistage GN algorithm and a ranking method, which exploit information in different parts of a paper. Our system achieved a promising AUC of 0.43471. Using the multistage GN algorithm, we have been able to improve system performance (AUC) by 1.719 percent compared to a one-stage GN algorithm. Our experimental results also show that with full text, versus abstract only, INT AUC performance was 22.6 percent higher.
36 citations
TL;DR: This paper examined the nature and value of empathic communication in call center dyads and found that attentive and cognitive responses could engender highly positive responses although customers' need for them varied tremendously.
Abstract: This study examines the nature and value of empathic communication in call center dyads. Our research site was a multinational financial services call center that we came to know through grounded study techniques, including analyses of 289 stressful calls. Examining calls as communication genre revealed that agents and customers have conflicting organizational, service, and efficiency needs that undermine communication. But three types of empathic expression can mitigate these conflicts in some interactions. Affective expressions, such as “I’m sorry,” were less effectual, but attentive and cognitive responses could engender highly positive responses although customers’ need for them varied tremendously. Thus, customer service agents must use both diagnostic and enactment skills to perform empathic communication effectively, a coupling that we call empathywork.
36 citations
TL;DR: The results indicate precision of .93, recall of .71, and accuracy of .76, which is promising for pedagogical applications of the analyzer, that is, providing learners with automated formative feedback specific to causal discourse.
Abstract: Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners’ causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of evaluating causal discourse. The authors of the present study attempt to fill in this gap by (1) developing an automated causal discourse analyzer and (2) investigating how accurately the analyzer processes learners’ causal discourse in academic writing. The accuracy of the analyzer is evaluated on cause-and-effect essays written by 17 non-native undergraduate students. The results indicate precision of .93, recall of .71, and accuracy of .76, which is promising for pedagogical applications of the analyzer, that is, providing learners with automated formative feedback specific to causal discourse.
36 citations