Mining Language

Mining Language

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  • Author: Allison Margaret Bigelow
  • Publisher: UNC Press Books
  • ISBN: 1469654393
  • Category : History
  • Languages : en
  • Pages : 377

Mineral wealth from the Americas underwrote and undergirded European colonization of the New World; American gold and silver enriched Spain, funded the slave trade, and spurred Spain’s northern European competitors to become Atlantic powers. Building upon works that have narrated this global history of American mining in economic and labor terms, Mining Language is the first book-length study of the technical and scientific vocabularies that miners developed in the sixteenth and seventeenth centuries as they engaged with metallic materials. This language-centric focus enables Allison Bigelow to document the crucial intellectual contributions Indigenous and African miners made to the very engine of European colonialism. By carefully parsing the writings of well-known figures such as Cristóbal Colón and Gonzalo Fernández de Oviedo y Valdés and lesser-known writers such Álvaro Alonso Barba, a Spanish priest who spent most of his life in the Andes, Bigelow uncovers the ways in which Indigenous and African metallurgists aided or resisted imperial mining endeavors, shaped critical scientific practices, and offered imaginative visions of metalwork. Her creative linguistic and visual analyses of archival fragments, images, and texts in languages as diverse as Spanish and Quechua also allow her to reconstruct the processes that led to the silencing of these voices in European print culture.


Natural Language Processing and Text Mining

Natural Language Processing and Text Mining

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  • Author: Anne Kao
  • Publisher: Springer Science & Business Media
  • ISBN: 1846287545
  • Category : Computers
  • Languages : en
  • Pages : 272

Natural Language Processing and Text Mining not only discusses applications of Natural Language Processing techniques to certain Text Mining tasks, but also the converse, the use of Text Mining to assist NLP. It assembles a diverse views from internationally recognized researchers and emphasizes caveats in the attempt to apply Natural Language Processing to text mining. This state-of-the-art survey is a must-have for advanced students, professionals, and researchers.


Sentiment Analysis and Opinion Mining

Sentiment Analysis and Opinion Mining

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  • Author: Bing Liu
  • Publisher: Morgan & Claypool Publishers
  • ISBN: 1608458849
  • Category : Computers
  • Languages : en
  • Pages : 185

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography


Methods for Mining and Summarizing Text Conversations

Methods for Mining and Summarizing Text Conversations

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  • Author: Giuseppe Carenini​‌
  • Publisher: Morgan & Claypool Publishers
  • ISBN: 160845391X
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 132

Due to the Internet Revolution, human conversational data -- in written forms -- are accumulating at a phenomenal rate. At the same time, improvements in speech technology enable many spoken conversations to be transcribed. Individuals and organizations engage in email exchanges, face-to-face meetings, blogging, texting and other social media activities. The advances in natural language processing provide ample opportunities for these "informal documents" to be analyzed and mined, thus creating numerous new and valuable applications. This book presents a set of computational methods to extract information from conversational data, and to provide natural language summaries of the data. The book begins with an overview of basic concepts, such as the differences between extractive and abstractive summaries, and metrics for evaluating the effectiveness of summarization and various extraction tasks. It also describes some of the benchmark corpora used in the literature. The book introduces extraction and mining methods for performing subjectivity and sentiment detection, topic segmentation and modeling, and the extraction of conversational structure. It also describes frameworks for conducting dialogue act recognition, decision and action item detection, and extraction of thread structure. There is a specific focus on performing all these tasks on conversational data, such as meeting transcripts (which exemplify synchronous conversations) and emails (which exemplify asynchronous conversations). Very recent approaches to deal with blogs, discussion forums and microblogs (e.g., Twitter) are also discussed. The second half of this book focuses on natural language summarization of conversational data. It gives an overview of several extractive and abstractive summarizers developed for emails, meetings, blogs and forums. It also describes attempts for building multi-modal summarizers. Last but not least, the book concludes with thoughts on topics for further development. Table of Contents: Introduction / Background: Corpora and Evaluation Methods / Mining Text Conversations / Summarizing Text Conversations / Conclusions / Final Thoughts


Sentiment Analysis

Sentiment Analysis

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  • Author: Bing Liu
  • Publisher: Cambridge University Press
  • ISBN: 1108787282
  • Category : Computers
  • Languages : en
  • Pages : 451

Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.


Text Mining with R

Text Mining with R

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  • Author: Julia Silge
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1491981628
  • Category : Computers
  • Languages : en
  • Pages : 193

Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.


Mining Software Specifications

Mining Software Specifications

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  • Author: David Lo
  • Publisher: CRC Press
  • ISBN: 1439806276
  • Category : Computers
  • Languages : en
  • Pages : 460

An emerging topic in software engineering and data mining, specification mining tackles software maintenance and reliability issues that cost economies billions of dollars each year. The first unified reference on the subject, Mining Software Specifications: Methodologies and Applications describes recent approaches for mining specifications of sof


Western Mining

Western Mining

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  • Author: Otis E. Young, Jr.
  • Publisher: University of Oklahoma Press
  • ISBN: 9780806113524
  • Category : Technology & Engineering
  • Languages : en
  • Pages : 372

Here, for the first time, is a clear account in words and pictures of the methods by which gold and silver were extracted and processed in the Old West. The author describes the early days of Spanish and Indian mining and the wild era inaugurated by the American prospector who rushed west to get rich quick, ending with the year 1893, when repeal of the Sherman Silver Purchase Act virtually closed the mining frontier. The account gives in laymen’s language the techniques employed in prospecting, placering, lode mining, and milling, particularly those employed by the Spaniards, Indians, and Cornishmen, and shows how the ever-practical Americans adapted and improved them. Special attention is given to the methods employed in the California and Montana gold fields, Colorado and the Comstock Lode, the Black Hills, and Tombstone, Arizona. In these pages the reader also meets some of the unforgettable personalities whose lives enriched (and sometimes impoverished) the mining camps.


Mining Social Media

Mining Social Media

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  • Author: Lam Thuy Vo
  • Publisher: No Starch Press
  • ISBN: 1593279167
  • Category : Computers
  • Languages : en
  • Pages : 210

BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.


Mining the Social Web

Mining the Social Web

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  • Author: Matthew Russell
  • Publisher: "O'Reilly Media, Inc."
  • ISBN: 1449388345
  • Category : Computers
  • Languages : en
  • Pages : 356

Facebook, Twitter, and LinkedIn generate a tremendous amount of valuable social data, but how can you find out who's making connections with social media, what they’re talking about, or where they’re located? This concise and practical book shows you how to answer these questions and more. You'll learn how to combine social web data, analysis techniques, and visualization to help you find what you've been looking for in the social haystack, as well as useful information you didn't know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, and LinkedIn Learn how to employ easy-to-use Python tools to slice and dice the data you collect Explore social connections in microformats with the XHTML Friends Network Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits "Let Matthew Russell serve as your guide to working with social data sets old (email, blogs) and new (Twitter, LinkedIn, Facebook). Mining the Social Web is a natural successor to Programming Collective Intelligence: a practical, hands-on approach to hacking on data from the social Web with Python." --Jeff Hammerbacher, Chief Scientist, Cloudera "A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google