Text Analytics : Advances and Challenges. 1st ed. 2020

種類:

電子ブック

責任表示:

edited by Domenica Fioredistella Iezzi, Damon Mayaffre, Michelangelo Misuraca

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2020

著者名:

• Iezzi, Domenica Fioredistella.
• Mayaffre, Damon.
• Misuraca, Michelangelo.
• SpringerLink (Online service)

シリーズ名:

Studies in Classification, Data Analysis, and Knowledge Organization ;

ISBN:

9783030526801 [3030526801]    

注記:

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: Compari
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. .

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