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.
Arvustused
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)
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 Mayare 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 nance 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).
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 Masters 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 dAzur 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.
