Text Analytics: Advances and Challenges

ISBN-13: 9783030526795 / Angielski / Miękka / 2020 / 302 str.

Domenica Fioredistella Iezzi; Damon Mayaffre; Michelangelo Misuraca

Recenzje

"Readership: Graduate and advanced undergraduate statistics students, as well as practitioners. ... Text Analytics: Advances and Challenges is an interesting read. ... For students of text analysis and practitioners who are interested in applying text analysis methods to real problems, this text will be of interest." (Jordan Rodu, International Statistical Review, June 2, 2021)

Spis treści

​​PART - 1 :Techniques, Methods and Models

Chapter 1 - Text Analytics: present, past, and future (Domenica Fioredistella Iezzi, Livia Celardo) 

Chapter 2 - Unsupervised analytic strategies to explore large document collections (Michelangelo Misuraca and Maria Spano) 

Chapter 3 - Studying narrative flows by Text Analysis e Network Text Analysis (Cristiano Felaco) 

Chapter 4 - Key passages : from statistics to deep learning (Laurent Vanni, Marco Corneli, Dominique Longree, Damon Mayaffre and Frederic Precioso)

Chapter 5 - Concentration indices for dialogue dominance phenomena in TV series: the case of the Big Bang Theory (Andrea Fronzetti Colladon and Maurizio Naldi)

Chapter 6 - A conversation analysis of interactions in personal finance forums (Maurizio Naldi)

​PART - 2 :Dictionaries and specific languages

Chapter 7 - Big Corpora and Text Clustering: the Italian accounting jurisdiction case (Domenica Fioredistella Iezzi, Rosamaria Berté)

Chapter 8 - Lexicometric paradoxes of frequency: Comparing VoBIS and NVdB  (Luisa Revelli)

Chapter 9 - Emotions and dense words in emotional text analysis: An invariant or a contextual relationship? (Nadia Battisti, Francesca Dolcetti)

Chapter 10 – Text Mining of Public Administration documents: preliminary results on judgements (Romano Maria Francesca, Baldassarini Antonella, Pavone Pasquale)

Chapter 11 - Using the First Axis of a Correspondence Analysis as an Analytic Tool (Bénédicte Pincemin, Alexei Lavrentiev and Céline Guillot-Barbance)

Chapter 12 - Discursive Functions of French Modal Forms: What can Correspondence Analysis tell us about Genre and Diachronic Variation? (Corinne Rossari, Ljiljana Dolamic, Annalena Hütsch, Claudia Ricci, Dennis Wandel)

​PART - 3 :Multilingual Text Analysis

Chapter 13 - How to think about finding a sign for a multilingual and multimodal French written / French sign language platform? (Cédric Moreau)

Chapter 14 - Corpus in “natural” language vs “translation” language: LBC corpora, a tool for bilingual lexicographic writing (Annick Farina, Riccardo Billero)

Chapter 15 - The conditional perfect, a quantitative analysis in English-French comparable-parallel corpora (Daniel Henkel)

Chapter 16 - Repeated and anaphoric segments applied to trilingual knowledge extraction (Lionel Shen)

Chapter 17 - Looking for topics: a brief review (Ludovic Lebart)

​PART - 4 :Applications

Chapter 18 - Where are the Social Sciences going to? The Case of the EU-Funded SSH Research Projects (Matteo Gerli)

Chapter 19 - Topic modeling of Twitter conversations: the case of the National University of Colombia (Eliana Sanandres)

Chapter 20 - Analysing occupational safety culture through mass media monitoring (Livia Celardo, Rita Vallerotonda, Daniele De Santis, Claudio Scarici, Antonio Leva)

Chapter 21 – What volunteers do? A textual analysis of voluntary activities in the Italian context (Francesco Santelli, Giancarlo Ragozini, Marco Musella)

Chapter 22 - Free text analysis in electronic clinical   documentation (Antonella Bitetto, Luigi Bollani)

Chapter 23 - Educational culture and job market: A text mining approach (Barbara Cordella, Francesca Greco, Paolo Meoli, Vittorio Palermo & Massimo Grasso)

O autorze

Domenica Fioredistella Iezzi is an Associate Professor of Social Statistics at the Department of Enterprise Engineering Mario Lucertini, Tor Vergata University of Rome, Italy. She teaches courses on exploratory methods for data analysis and social media analytics. She is qualified as a Full Professor of Demography and Social Statistics and has been the director of the Master’s program in Data Science since 2014. A past advisor to the Italian Society of Demography and Statistics and the Italian Statistical Society, she has authored numerous scientific articles in national and international journals. Her main research topics include text clustering and social indicators.

Damon Mayaffre is a CNRS researcher and a Professor at the Nice Côte d’Azur University, France. He is a specialist in the statistical analysis of textual data and has published several books on the political discourse of French presidents.

Michelangelo Misuraca is an Associate Professor of Statistics for Social Sciences at the Department of Business Administration and Law, University of Calabria, Italy. He has taught courses on textual statistics and statistics for the social sciences at the University of Naples Federico II and the University of Calabria. A Fellow of the Italian Statistical Society and of the Royal Statistical Society, his research interests are mainly in the areas of textual statistics, text mining and social media mining.

Blurb

Focusing on methodologies, applications and challenges of textual data analysis and related fields, this book gathers selected and peer-reviewed contributions presented at the 14th International Conference on Statistical Analysis of Textual Data (JADT 2018), held in Rome, Italy, on June 12-15, 2018. Statistical analysis of textual data is a multidisciplinary field of research that has been mainly fostered by statistics, linguistics, mathematics and computer science. The respective sections of the book focus on techniques, methods and models for text analytics, dictionaries and specific languages, multilingual text analysis, and the applications of text analytics. The interdisciplinary contributions cover topics including text mining, text analytics, network text analysis, information extraction, sentiment analysis, web mining, social media analysis, corpus and quantitative linguistics, statistical and computational methods, and textual data in sociology, psychology, politics, law and marketing.