Michael W. Berry Livres

During the early days of the COVID-19 health crisis, Fang Fangs Wuhan Diary provided an important portal for people around the world to understand the outbreak, local response, and how the novel coronavirus was impacting everyday people. But when news of the international publication of Wuhan Diary appeared online in early April of 2020, Fang Fangs writings became the target of a series of online attacks by "Chinese ultra-nationalists." Over time, these attacks morphed into one of the most sophisticated and protracted hate Campaigns against a Chinese writer in decades. Meanwhile, as controversy around Wuhan Diary swelled in China, the author was transformed into a global icon, honored by the BBC as one of the most influential women of 2020 and featured in stories by dozens of international news outlets. This book, by the translator of Wuhan Diary into English, alternates between a first-hand account of the translation process and more critical observations on how a diary became a lightning rod for fierce political debate and the target of a sweeping online campaign that many described as a "cyber Cultural Revolution." Eventually, even Berry would be pulled into the attacks and targeted by thousands of online trolls. This book answers the questions: why would an online lockdown diary elicit such a strong reaction among Chinese netizens? How did the controversy unfold and evolve? Who was behind it? And what can we learn from the "Fang Fang Incident" about contemporary Chinese politics and society? The book will be of interest to students and scholars of translation, as well as anyone with special interest in translation, US-Chinese relations, or internet culture more broadly

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.

This book constitutes the refereed proceedings of the International Conference on Soft Computing in Data Science, SCDS 2015, held in Putrajaya, Malaysia, in September 2015. The 25 revised full papers presented were carefully reviewed and selected from 69 submissions. The papers are organized in topical sections on data mining; fuzzy computing; evolutionary computing and optimization; pattern recognition; human machine interface; hybrid methods.