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A revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for \"black girls\"—what will you find? \"Big Booty\" and other sexually explicit terms are likely to come up as top search terms. But, if you type in \"white girls,\" the results are radically different. The suggested porn sites and un-moderated discussions about \"why black women are so sassy\" or \"why black women are so angry\" presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance—operating as a source for email, a major vehicle for primary and secondary school learning, and beyond—understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.

In Web 2.0 users not only make heavy use of Col-laborative Information Services in order to create, publish and share digital information resources - what is more, they index and represent these re-sources via own keywords, so-called tags. The sum of this user-generated metadata of a Collaborative Information Service is also called Folksonomy. In contrast to professionally created and highly struc-tured metadata, e.g. subject headings, thesauri, clas-sification systems or ontologies, which are applied in libraries, corporate information architectures or commercial databases and which were developed according to defined standards, tags can be freely chosen by users and attached to any information resource. As one type of metadata Folksonomies provide access to information resources and serve users as retrieval tool in order to retrieve own re-sources as well as to find data of other users. The book delivers insights into typical applications of Folksonomies, especially within Collaborative Information Services, and discusses the strengths and weaknesses of Folksonomies as tools of knowl-edge representation and information retrieval. More-over, it aims at providing conceptual considerations for solving problems of Folksonomies and presents how established methods of knowledge representa-tion and models of information retrieval can successfully be transferred to them.

What did you do before Google? The rise of Google as the dominant Internet search provider reflects a generationally-inflected notion that everything that matters is now on the Web, and should, in the moral sense of the verb, be accessible through search. In this theoretically nuanced study of search technology's broader implications for knowledge production and social relations, the authors shed light on a culture of search in which our increasing reliance on search engines influences not only the way we navigate, classify, and evaluate Web content, but also how we think about ourselves and the world around us, online and off. Ken Hillis, Michael Petit, and Kylie Jarrett seek to understand the ascendancy of search and its naturalization by historicizing and contextualizing Google's dominance of the search industry, and suggest that the contemporary culture of search is inextricably bound up with a metaphysical longing to manage, order, and categorize all knowledge. Calling upon this nexus between political economy and metaphysics, Google and the Culture of Search explores what is at stake for an increasingly networked culture in which search technology is a site of knowledge and power.

Since the beginning of the computer age, researchers from many disciplines have sought to facilitate people's use of computers and to provide ways for scientists to make sense of the immense quantities of data coming out of them. One gainful result of these efforts has been the field of information visualization, whose technology is increasingly applied in scientific research, digital libraries, data mining, financial data analysis, market studies, manufacturing production control, and data discovery.This book collects 38 of the key papers on information visualization from a leading and prominent research lab, the University of Maryland's Human-Computer Interaction Lab (HCIL). Celebrating HCIL's 20th anniversary, this book presents a coherent body of work from a respected community that has had many success stories with its research and commercial spin-offs. Each chapter contains an introduction specifically written for this volume by two leading HCI researchers, to describe the connections among those papers and reveal HCIL's individual approach to developing innovations. *Presents key ideas, novel interfaces, and major applications of information visualization tools, embedded in inspirational prototypes.*Techniques can be widely applied in scientific research, digital libraries, data mining, financial data analysis, business market studies, manufacturing production control, drug discovery, and genomic studies.*Provides an \"insider\" view to the scientific process and evolution of innovation, as told by the researchers themselves.*This work comes from the prominent and high profile University of Maryland's Human Computer Interaction Lab

Skilled researchers, journalists, and subject experts have come together in this follow-up to Web of Deception to reveal important lessons for staying safe and retaining privacy online. In the wake of the social media popularity boom—epitomized by MySpace, eBay, and Craigslist and accelerating with Facebook and Twitter—the success of internet con artists and thieves has been quick to follow. Manipulators have been provided with the tools and targets to perpetrate hoaxes and con games on an ever larger scale. An invaluable guide to safe internet usage, this resource explains the importance of guarding privacy and identity online, spotting misinformation, avoiding charity scams, and evaluating websites.

Purpose – The purpose of this study is to examine how graduate students perceive and use Google Scholar. Google Scholar has provided a convenient alternative for finding scholarly documents since its inception in 2004 and has become a favoured tool for numerous academics. Knowledge of patrons’ usage patterns and attitudes towards Google Scholar will assist librarians in designing appropriate instruction programmes to improve students’ research abilities. Design/methodology/approach – In this study, 32 graduate students from the National Taiwan University were interviewed whose fields of study are the humanities (10), social sciences (11) and science and technology (11). Findings – Students prefer the usability of Google Scholar over library databases. However, they appreciate the quality of documents retrieved from library databases and regard these databases as crucial tools for finding scholarly documents. Science and technology students favoured Google Scholar more than those who study the humanities and social sciences. Research limitations/implications – This study only examines the perceptions and behaviour of graduate students. Future studies should include undergraduate students to investigate their use of Google Scholar, thereby obtaining a comprehensive understanding of various patrons of university libraries. Practical implications – This study shows that graduate students appreciate and use Google Scholar to find scholarly documents, although some students experience difficulties. The findings of this study may assist university libraries in improving their instruction programmes. Originality/value – The majority of previous studies have focused on coverage, quality and retrieval performance of Google Scholar. However, this study evaluates Google Scholar from a user’s perspective.

Background Health policy and systems research (HPSR) is an inherently cross-disciplinary field of investigation. However, conflicting conceptualisations about inter-, multi- and transdisciplinary research have contributed to confusion about the characteristics of cross-disciplinary approaches in HPSR. This review was conducted to (1) define the characteristic features of context–mechanism–outcome (CMO) configurations in cross-disciplinary HPSR, (2) develop criteria for evaluating cross-disciplinarity and (3) synthesise emerging challenges of the approach. Method The paper is a critical realist synthesis conducted in three phases, as follows: (1) scoping the literature, (2) searching for and screening the evidence, and (3) extracting and synthesising the evidence. Five databases, namely the International Bibliography of the Social Sciences and Web of Science, PubMed central, Embase and CINHAL, and reference lists of studies that qualified for inclusion in the review were searched. The search covered peer-reviewed original research, reviews, commentary papers, and institutional or government reports published in English between January 1998 and January 2020. Results A total of 7792 titles were identified in the online search and 137 publications, comprising pilot studies as well as anecdotal and empirical literature were selected for the final review. The review draws attention to the fact that cross-disciplinary HPSR is not defined by individual characteristics but by the combination of a particular type of research question and setting (context), a specific way of researchers working together (mechanism), and research output (outcome) that is superior to what could be achieved under a monodisciplinary approach. This CMO framework also informs the criteria for assessing whether a given HPSR is truly cross-disciplinary. The challenges of cross-disciplinary HPSR and their accompanying coping mechanisms were also found to be context driven, originating mainly from conceptual disagreements, institutional restrictions, communication and information management challenges, coordination problems, and resource limitations. Conclusion These findings have important implications. First, the CMO framework of cross-disciplinary HPSR can provide guidance for researchers engaging in new projects and for policy-makers using their findings. Second, the proposed criteria for evaluating theory and practice of cross-disciplinary HPSR may inform the systematic development of new research projects and the structured assessment of existing ones. Third, a better understanding of the challenges of cross-disciplinary HPSR and potential response mechanisms may help researchers to avoid these problems in the future.

Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. * Shows how to decompose current business strategies in order to link big data initiatives to the organization's value creation processes * Explores different value creation processes and models * Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles * Provides methodology worksheets and exercises so readers can apply techniques * Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.

Algorithms for Automating Open Source Intelligence (OSINT) presents information on the gathering of information and extraction of actionable intelligence from openly available sources, including news broadcasts, public repositories, and more recently, social media.