Mouvements sociaux sur Twitter et Digital Methods : des données aux analyses

Terminal ◽  
2021 ◽  
Author(s):  
Lucie Loubère
Keyword(s):  
Mouvements Sociaux ◽  
Digital Methods

Explanatory Annotation of Literary Texts and the Reader: Seven Types of Problems

2017 ◽  
Vol 11 (2) ◽  
pp. 212-232 ◽  
Author(s):  
Matthias Bauer ◽  
Angelika Zirker
Keyword(s):  
Text Comprehension ◽  
Best Practice ◽  
Literary Texts ◽  
Structured Information ◽  
Digital Methods ◽  
Common Problems

While most literary scholars wish to help readers understand literary texts by providing them with explanatory annotations, we want to go a step further and enable them, on the basis of structured information, to arrive at interpretations of their own. We therefore seek to establish a concept of explanatory annotation that is reader-oriented and combines hermeneutics with the opportunities provided by digital methods. In a first step, we are going to present a few examples of existing annotations that apparently do not take into account readerly needs. To us, they represent seven types of common problems in explanatory annotation. We then introduce a possible model of best practice which is based on categories and structured along the lines of the following questions: What kind(s) of annotations do improve text comprehension? Which contexts must be considered when annotating? Is it possible to develop a concept of the reader on the basis of annotations—and can, in turn, annotations address a particular kind of readership, i.e.: in how far can annotations be(come) individualised?

Reverse mediations: digital methods of social research for digital citizenship

2015 ◽  
Vol 23 ◽  
Author(s):  
Marina Pantoja Boechat ◽  
Débora De Carvalho Pereira
Keyword(s):  
Information Technologies ◽  
Social Research ◽  
Social Reality ◽  
Digital Citizenship ◽  
Social Analysis ◽  
Hegemonic Discourse ◽  
Methods Of Social Research ◽  
Digital Methods ◽  
The Many

Our society is heavily mediated by information technologies, so the simplest interactions become traceable, which collaborates to a deluge of data. They represent an abundant source for social analysis and an unparalleled opportunity for citizens to access, produce and disseminate information. Nevertheless, all this affluence of data, for presenting itself in a scattered way, also poses significant difficulties for achieving an integrated view of social reality and its interactions, and is organized in many competing interfaces and information architectures, that may produce, reinforce and disseminate ideologies, hegemonic discourse and platform biases. We identify an emerging field of dispute of the place of mediation of the many flows of information, and efforts for repurposing and restructuring these flows over the seamless structuring of different competing architectures. In order to describe some of these efforts, we draw examples from the field of controversy mapping, and propose the concept of reverse mediation.

Mouvements sociaux et dépendance idéologique en Amérique latine

1976 ◽  
Vol 39 (1) ◽  
pp. 155-165
Author(s):  
Elena Hernandez-Casas de Benenati
Keyword(s):  
Mouvements Sociaux ◽  
Amérique Latine ◽  
Amerique Latine

Considérations sur les théories des mouvements sociaux

Politix ◽  
1990 ◽  
Vol 3 (9) ◽  
pp. 74-80 ◽  
Author(s):  
Alessandro Pizzorno
Keyword(s):  
Mouvements Sociaux

Monde ouvrier contemporain et mouvements sociaux

Tiers-Monde ◽  
1989 ◽  
Vol 30 (119) ◽  
pp. 613-633 ◽  
Author(s):  
Gérard Heuzé
Keyword(s):  
Mouvements Sociaux

The Use of Digital Clinical Trial Methods in the Evaluation of Digital Therapeutics: A Scoping Review (Preprint)

2019 ◽  
Author(s):  
Allison Hirsch ◽  
Mahip Grewal ◽  
Anthony James Martorell ◽  
Brian Michael Iacoviello
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Clinical Research ◽  
Scoping Review ◽  
Digital Technologies ◽  
Good Clinical Practice ◽  
The United States ◽  
Clinical Trial Research ◽  
Digital Methods ◽  
Clinical Trial Methods

BACKGROUND Digital Therapeutics (DTx) provide evidence based therapeutic health interventions that have been clinically validated to deliver therapeutic outcomes, such that the software is the treatment. Digital methodologies are increasingly adopted to conduct clinical trials due to advantages they provide including increases in efficiency and decreases in trial costs. Digital therapeutics are digital by design and can leverage the potential of digital and remote clinical trial methods. OBJECTIVE The principal purpose of this scoping review is to review the literature to determine whether digital technologies are being used in DTx clinical research, which type are being used and whether publications are noting any advantages to their use. As DTx development is an emerging field there are likely gaps in the knowledge base regarding DTx and clinical trials, and the purpose of this review is to illuminate those gaps. A secondary purpose is to consider questions which emerged during the review process including whether fully remote digital clinical research is appropriate for all health conditions and whether digital clinical trial methods are inline with the principles of Good Clinical Practice. METHODS 1,326 records were identified by searching research databases and 1,227 reviewed at the full-article level in order to determine if they were appropriate for inclusion. Confirmation of clinical trial status, use of digital clinical research methods and digital therapeutic status as well as inclusion and exclusion criteria were applied in order to determine relevant articles. Digital methods employed in DTx research were extracted from each article and these data were synthesized in order to determine which digital methods are currently used in clinical trial research. RESULTS After applying our criteria for scoping review inclusion, 11 articles were identified. All articles used at least one form of digital clinical research methodology enabling an element of remote research. The most commonly used digital methods are those related to recruitment, enrollment and the assessment of outcomes. A small number of articles reported using other methods such as online compensation (n = 3), or digital reminders for participants (n = 5). The majority of digital therapeutics clinical research using digital methods is conducted in the United States and increasing number of articles using digital methods are published each year. CONCLUSIONS Digital methods are used in clinical trial research evaluating DTx, though not frequently as evidenced by the low proportion of articles included in this review. Fully remote clinical trial research is not yet the standard, more frequently authors are using partially remote methods. Additionally, there is tremendous variability in the level of detail describing digital methods within the literature. As digital technologies continue to advance and the clinical research DTx literature matures, digital methods which facilitate remote research may be used more frequently.

scholarly journals Author identification of short texts using dependency treebanks without vocabulary

2019 ◽  
Vol 35 (4) ◽  
pp. 812-825 ◽  
Author(s):  
Robert Gorman
Keyword(s):  
Text Classification ◽  
Authorship Attribution ◽  
Support Vector ◽  
Ancient Greek ◽  
Combinatorial Explosion ◽  
Independent Variables ◽  
Author Identification ◽  
Important Addition ◽  
Digital Methods ◽  
And Control

Abstract How to classify short texts effectively remains an important question in computational stylometry. This study presents the results of an experiment involving authorship attribution of ancient Greek texts. These texts were chosen to explore the effectiveness of digital methods as a supplement to the author’s work on text classification based on traditional stylometry. Here it is crucial to avoid confounding effects of shared topic, etc. Therefore, this study attempts to identify authorship using only morpho-syntactic data without regard to specific vocabulary items. The data are taken from the dependency annotations published in the Ancient Greek and Latin Dependency Treebank. The independent variables for classification are combinations generated from the dependency label and the morphology of each word in the corpus and its dependency parent. To avoid the effects of the combinatorial explosion, only the most frequent combinations are retained as input features. The authorship classification (with thirteen classes) is done with standard algorithms—logistic regression and support vector classification. During classification, the corpus is partitioned into increasingly smaller ‘texts’. To explore and control for the possible confounding effects of, e.g. different genre and annotator, three corpora were tested: a mixed corpus of several genres of both prose and verse, a corpus of prose including oratory, history, and essay, and a corpus restricted to narrative history. Results are surprisingly good as compared to those previously published. Accuracy for fifty-word inputs is 84.2–89.6%. Thus, this approach may prove an important addition to the prevailing methods for small text classification.

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