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Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance
This study examines whether user-generated content (UGC) is related to stock market performance, which metric of UGC has the strongest relationship, and what the dynamics of the relationship are. We aggregate UGC from multiple websites over a four-year period across 6 markets and 15 firms. We derive multiple metrics of UGC and use multivariate time-series models to assess the relationship between UGC and stock market performance.
Volume of chatter significantly leads abnormal returns by a few days (supported by Granger causality tests). Of all the metrics of UGC, volume of chatter has the strongest positive effect on abnormal returns and trading volume. The effect of negative and positive metrics of UGC on abnormal returns is asymmetric. Whereas negative UGC has a significant negative effect on abnormal returns with a short \"wear-in\" and long \"wear-out,\" positive UGC has no significant effect on these metrics. The volume of chatter and negative chatter have a significant positive effect on trading volume. Idiosyncratic risk increases significantly with negative information in UGC. Positive information does not have much influence on the risk of the firm. An increase in off-line advertising significantly increases the volume of chatter and decreases negative chatter. These results have important implications for managers and investors.
Journal Article
Handbook of research on opinion mining and text analytics on literary works and social media
\"This book uses artificial intelligence and big data analytics to conduct opinion mining and text analytics on literary works and social media, focusing on theories, method, applications and approaches of data analytic techniques that can be used to extract and analyze data from literary books and social media, in a meaningful pattern\"-- Provided by publisher.
Book
Text mining in practice with R
A reliable, cost-effective approach to extracting priceless business information from all sources of text Excavating actionable business insights from data is a complex undertaking, and that complexity is magnified by an order of magnitude when the focus is on documents and other text information.
eBook
Regex quick syntax reference : understanding and using regular expressions
\"This quick guide to regular expressions is a condensed code and syntax reference for an important programming technique. It demonstrates regex syntax in a well-organized format that can be used as a handy reference showing you how to execute regexes in many languages, including JavaScript, Python, Java, and C#. The Regex Quick Syntax Reference features short, focused code examples that show you how to use regular expressions to validate user input, split strings, parse input, and match patterns. Utilizing regular expressions to deal with search/replace and filtering data for backend coding is also covered. You won't find any bloated samples, drawn out history lessons, or witty stories in this book. What you will find is a language reference that is concise and highly accessible. The book is packed with useful information and is a must-have for any programmer. You will: formulate an expression; work with arbitrary char classes, disjunctions, and operator precedence; execute regular expressions and visualize using finite state machines; use greedy, lazy, and possessive repeat modifiers for looping in regular expressions; handle substring extraction from regex using Perl 6 capture groups, capture substrings, and reuse substrings.\"--Page 4 of cover.
Book
The Ultimate Guide to Adobe Acrobat DC
PDFs have become the standard for creating, analyzing, storing, and exchanging digital documents, for filing documents in courts with electronic filing systems, and for many other uses. The completely updated second edition of The Ultimate Guide to Adobe® Acrobat® DC includes instructions for Windows and Mac users. This practical resource provides step-by-step instructions and nearly 300 screenshots showing how to get the most from Acrobat, from its most common tools to its most advanced features.The book will introduce you to the product's many benefits, including:Editing and annotating PDF filesSharing PDF filesSending PDF files electronicallyRedacting and Bates numbering documentsAllowing users with free Adobe® Reader to fill forms, add comments, and suggest revisionsInserting notes and commentsStoring e-mailSecuring PDFs to prevent unauthorized persons from accessing the filesSecuring documents of all types to prevent the disclosure of confidential informationRemoving metadata and other information from PDF filesPreventing other users from making changes to PDF filesImproving workflow and increasing productivityReducing the use of paperThe most comprehensive guide available, the fully updated second edition of The Ultimate Guide to Adobe® Acrobat® DC discusses and demonstrates the features that all businesses and law offices use, and explains and illustrates what the features are, why they are important, and how to use them.
eBook
Subjective well-being and social media
\"Subjective Well-Being and Social Media shows how, by exploiting the unprecedented amount of information provided by the social networking sites, it is possible to build new composite indicators of subjective well-being. These new social media indicators are complementary to official statistics and surveys, whose data are collected at very low temporary and geographical resolution. The book also explains in full details how to solve the problem of selection bias coming from social media data. Mixing textual analysis, machine learning and time series analysis, the book also shows how to extract both the structural and the temporary components of subjective well-being. Cross-country analysis confirms that well-being is a complex phenomenon that is governed by macroeconomic and health factors, ageing, temporary shocks and cultural and psychological aspects. As an example, the last part of the book focuses on the impact of the prolonged stress due to the COVID-19 pandemic on subjective well-being in both Japan and Italy. Through a data science approach, the results show that a consistent and persistent drop occurred throughout 2020 in the overall level of well-being in both countries. The methodology presented in this book: enables social scientists and policy makers to know what people think about the quality of their own life, minimizing the bias induced by the interaction between the researcher and the observed individuals; being language-free, it allows for comparing the well-being perceived in different linguistic and socio-cultural contexts, disentangling differences due to objective events and life conditions from dissimilarities related to social norms or language specificities; provides a solution to the problem of selection bias in social media data through a systematic approach based on time-space small area estimation models. The book comes also with replication R scripts and data. Stefano M. Iacus is full professor of Statistics at the University of Milan, on leave at the Joint Research Centre of the European Commission. Former R-core member (1999-2017) and R Foundation Member. Giuseppe Porro is full professor of Economic Policy at the University of Insubria. An earlier version of this project was awarded the Italian Institute of Statistics-Google prize for \"official statistics and big data\"\"-- Provided by publisher.
Book
Measurement of Text Similarity: A Survey
Text similarity measurement is the basis of natural language processing tasks, which play an important role in information retrieval, automatic question answering, machine translation, dialogue systems, and document matching. This paper systematically combs the research status of similarity measurement, analyzes the advantages and disadvantages of current methods, develops a more comprehensive classification description system of text similarity measurement algorithms, and summarizes the future development direction. With the aim of providing reference for related research and application, the text similarity measurement method is described by two aspects: text distance and text representation. The text distance can be divided into length distance, distribution distance, and semantic distance; text representation is divided into string-based, corpus-based, single-semantic text, multi-semantic text, and graph-structure-based representation. Finally, the development of text similarity is also summarized in the discussion section.
Journal Article
Annotation of scientific uncertainty using linguistic patterns
Scientific uncertainty is an integral part of the research process and inherent to the construction of new knowledge. In this paper, we investigate the ways in which uncertainty is expressed in articles and propose a new interdisciplinary annotation framework to categorize sentences containing uncertainty expressions along five dimensions. We propose a method for the automatic annotation of sentences based on linguistic patterns for identifying the expressions of scientific uncertainty that have been derived from a corpus study. We processed a corpus of 5956 articles from 22 journals in three different discipline groups, which were annotated using our automatic annotation method. We evaluate our annotation method and study the distribution of uncertainty expressions across the different journals and categories. The results show a predominant concentration of the distribution of the scientific uncertainty expressions in the Results and Discussion section (71.4%), followed by 12.5% of expressions in the Background section, and the largest proportion of uncertainty expressions, approximately 70.3%, are formed as author(s) statements. Our research contributes methodological advances and insights into the diverse manifestations of scientific uncertainty across disciplinary domains and provides a basis for ongoing exploration and refinement of the understanding of scientific uncertainty communication.
Journal Article