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.

This volume represents the first collection of empirical studies focusing on peer interaction for L2 learning. These studies aim to unveil the impact of mediating variables such as task type, mode of interaction, and social relationships on learners’ interactional behaviors and language development in this unique and pedagogically powerful learning context. To examine these issues, contributors employed quantitative, qualitative, and mixed-methods designs as well as cognitive, social, and sociocognitive theoretical frameworks. The majority of the studies are classroom based and were conducted in a rich array of settings covering five continents and encompassing a wide range of learner L1s and target languages. These settings include second and foreign language classrooms from primary to university level, content-based programs, online contexts, and after-school programs. To span the divide between research and practice, each study includes a section suggesting pedagogical implications.