Drawing Elena Ferrante's Profile. Workshop Proceedings, Padova, 7 September 2017

Elena Ferrante is an internationally acclaimed Italian novelist whose real identity has been kept secret by E/O publishing house for more than 25 years. Owing to her popularity, major Italian and foreign newspapers have long tried to discover her real identity. However, only a few attempts have been made to foster a scientific debate on her work. In 2016, Arjuna Tuzzi and Michele Cortelazzo led an Italian research team that conducted a preliminary study and collected a well-founded, large corpus of Italian novels comprising 150 works published in the last 30 years by 40 different authors. Moreover, they shared their data with a select group of international experts on authorship attribution, profiling, and analysis of textual data: Maciej Eder and Jan Rybicki (Poland), Patrick Juola (United States), Vittorio Loreto and his research team, Margherita Lalli and Francesca Tria (Italy), George Mikros (Greece), Pierre Ratinaud (France), and Jacques Savoy (Switzerland). The chapters of this volume report the results of this endeavour that were first presented during the international workshop Drawing Elena Ferrante's Profile in Padua on 7 September 2017 as part of the 3rd IQLA-GIAT Summer School in Quantitative Analysis of Textual Data. The fascinating research findings suggest that Elena Ferrante\u2019s work definitely deserves \u201cmany hands\u201d as well as an extensive effort to understand her distinct writing style and the reasons for her worldwide success

Sulle tracce di Elena Ferrante: questioni di metodo e primi risultati

This chapter illustrates the implementation of quantitative analysis methods on a corpus of modern Italian novels aimed to shed light on the identity of Elena Ferrante, the pen name of a very successful novelist whose real identity is still unknown. After a review of previous attempts conducted according to different approaches (based on lexical, contextual and thematic factors), in order to offset the impact of diatopic varieties of Italian the seven novels written by Elena Ferrante have been compared to 39 novels written by ten authors from Campania (Ferrante\u2019s region of origin) according to two methods: correspondence analysis and intertextual distance. Both methods show that Elena Ferrante\u2019s novels are more similar to Domenico Starnone\u2019s works than to the novels of any other author included in the corpus. In addition, a lexical analysis shows that, compared to the other authors, Ferrante and Starnone share the greatest number of lexical items used exclusively in their novels. Conclusively, the qualitative and quantitative approaches used in this study confirm that a similarity emerges between the novels published by Ferrante and Starnone after the early 1990s and paves the way to further research based on larger corpora of fiction as well as non-fictional texts

TECNOB: study design of a randomized controlled trial of a multidisciplinary telecare intervention for obese patients with type-2 diabetes

Obesity is one of the most important medical and public health problems of our time: it increases the risk of many health complications such as hypertension, coronary heart disease and type 2 diabetes, needs long-lasting treatment for effective results and involves high public and private costs. Therefore, it is imperative that enduring and low-cost clinical programs for obesity and related co-morbidities are developed and evaluated. METHODS/DESIGN: TECNOB (TEChnology for OBesity) is a comprehensive two-phase stepped down program enhanced by telemedicine for the long-term treatment of obese people with type 2 diabetes seeking intervention for weight loss. Its core features are the hospital-based intensive treatment (1-month), that consists of diet therapy, physical training and psychological counseling, and the continuity of care at home using new information and communication technologies (ICT) such as internet and mobile phones. The effectiveness of the TECNOB program compared with usual care (hospital-based treatment only) will be evaluated in a randomized controlled trial (RCT) with a 12-month follow-up. The primary outcome is weight in kilograms. Secondary outcome measures are energy expenditure measured using an electronic armband, glycated hemoglobin, binge eating, self-efficacy in eating and weight control, body satisfaction, healthy habit formation, disordered eating-related behaviors and cognitions, psychopathological symptoms and weight-related quality of life. Furthermore, the study will explore what behavioral and psychological variables are predictive of treatment success among those we have considered. DISCUSSION: The TECNOB study aims to inform the evidence-based knowledge of how telemedicine may enhance the effectiveness of clinical interventions for weight loss and related type-2 diabetes, and which type of obese patients may benefit the most from such interventions. Broadly, the study aims also to have a effect on the theoretical model behind the traditional health care service, in favor of a change towards a new "health care everywhere" approach

Antarctic ice sheet sensitivity to atmospheric CO2 variations in the early to mid-Miocene

Geological records from the Antarctic margin offer direct evidence of environmental variability at high southern latitudes and provide insight regarding ice sheet sensitivity to past climate change. The early to mid-Miocene (23-14 Mya) is a compelling interval to study as global temperatures and atmospheric CO2 concentrations were similar to those projected for coming centuries. Importantly, this time interval includes the Miocene Climatic Optimum, a period of global warmth during which average surface temperatures were 3-4 °C higher than today. Miocene sediments in the ANDRILL-2A drill core from the Western Ross Sea, Antarctica, indicate that the Antarctic ice sheet (AIS) was highly variable through this key time interval. A multiproxy dataset derived from the core identifies four distinct environmental motifs based on changes in sedimentary facies, fossil assemblages, geochemistry, and paleotemperature. Four major disconformities in the drill core coincide with regional seismic discontinuities and reflect transient expansion of grounded ice across the Ross Sea. They correlate with major positive shifts in benthic oxygen isotope records and generally coincide with intervals when atmospheric CO2 concentrations were at or below preindustrial levels (∼280 ppm). Five intervals reflect ice sheet minima and air temperatures warm enough for substantial ice mass loss during episodes of high (∼500 ppm) atmospheric CO2. These new drill core data and associated ice sheet modeling experiments indicate that polar climate and the AIS were highly sensitive to relatively small changes in atmospheric CO2 during the early to mid-Miocene

Functional model-based curve clustering for discovering temporal patterns in chronological corpora

In many applications of textual analysis corpora include texts having a chronological order. In a typical bag-of-words approach, data of chronological corpora are organized as word-type x time-point contingency tables where row frequencies represent the temporal trajectories of \u201cwords\u201d. In this setting major objectives of analysis are finding clusters of words portraying similar temporal patterns and possibly determining prototype patterns of evolution. We propose the application of a class of wavelet-based functional clustering mixed models to address specific issues posed by these data, which are highly sparse over time and individually heterogeneous, besides of being high-dimensional. Wavelet representation can accommodate a wider range of functional shapes, such as peak-like curves, and is more computationally efficient than splines. Moreover, it turns out to be useful in inspecting on different scales of the corpus temporal process. Procedures are tested using different text genres

Through the JASA's Looking-Glass, and What We Found There

This study is aimed at identifying sequential patterns for key-words included in chronological corpora and at grouping these word patterns in clusters. A model-based clustering procedure is proposed, with reference to titles of papers published by JASA (1888-2012)

Shaping the history of words

In textual analysis, many corpora include texts in chronological order and in many cases this temporal connotation is crucial to an understanding of their inner structure. In a typical bag-of-words approach, data are organized in contingency tables, the rows reporting the frequency of each word over time-points (shown in columns). These discrete data (temporal patterns for frequen-cies) may be viewed as continuous objects represented by functional relation-ships. This study aimed at identifying a specific sequential pattern for each word as a functional object and at grouping these word patterns in clusters. A model-based clustering procedure is proposed, with specific reference to a cor-pus of end-of-year messages delivered by the ten Presidents of the Italian Republic covering the period from 1949 to 2011

Identifying specific textual units of documents taken from large corpora. Comparing methods.

Actes JADT'2006 en ligne, (8th international Conference on Textual Data statistical Analysis