The guide includes information on aspects of the search that are common to all levels, with invaluable tips for those seeking their first or second faculty position. This new edition provides updated advice and addresses hot topics in the competitive job market of today, including the challenges faced by dual-career couples, job search issues for pregnant candidates, and advice on how to deal with gaps in a CV. The chapter on alternatives to academic jobs has been expanded, and sample resumes from individuals seeking nonfaculty positions are included.The book begins with an overview of the hiring process and a timetable for applying for academic positions. It then gives detailed information on application materials, interviewing, negotiating job offers, and starting the new job. Guidance throughout is aimed at all candidates, with frequent reference to the specifics of job searches in scientific and technical fields as well as those in the humanities and social sciences. Advice on seeking postdoctoral opportunities is also included.Perhaps the most significant contribution is the inclusion of sample vitas. "The Academic Job Search Handbook" describes the organization and content of the vita and includes samples from a variety of fields. In addition to CVs and research statements, new in this edition are a sample interview itinerary, a teaching portfolio, and a sample offer letter. The job search correspondence section has also been updated, and there is current information on Internet search methods and useful websites.

    In addition to changing how we live, these tools enable us to collect and process data about human behavior on a scale never before imaginable, offering entirely new approaches to core questions about social behavior. Bit by Bit is the key to unlocking these powerful methods--a landmark book that will fundamentally change how the next generation of social scientists and data scientists explores the world around us.Bit by Bit is the essential guide to mastering the key principles of doing social research in this fast-evolving digital age. In this comprehensive yet accessible book, Matthew Salganik explains how the digital revolution is transforming how social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations. He provides a wealth of real-world examples throughout and also lays out a principles-based approach to handling ethical challenges.Bit by Bit is an invaluable resource for social scientists who want to harness the research potential of big data and a must-read for data scientists interested in applying the lessons of social science to tomorrow's technologies.Illustrates important ideas with examples of outstanding researchCombines ideas from social science and data science in an accessible style and without jargonGoes beyond the analysis of "found" data to discuss the collection of "designed" data such as surveys, experiments, and mass collaborationFeatures an entire chapter on ethicsIncludes extensive suggestions for further reading and activities for the classroom or self-study

    This work contains components of the model, which include staffing models and strategy, staffing support systems (legal compliance, planning, job analysis and rewards), core staffing systems (recruitment, selection, employment), and staffing system and retention management.

    The authors help students learn key sociological concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables.

    It has sold 30,000 copies in each edition and will continue to reach a huge academic audience.In this renowned book, Everett M. Rogers, professor and chair of the Department of Communication & Journalism at the University of New Mexico, explains how new ideas spread via communication channels over time. Such innovations are initially perceived as uncertain and even risky. To overcome this uncertainty, most people seek out others like themselves who have already adopted the new idea. Thus the diffusion process consists of a few individuals who first adopt an innovation, then spread the word among their circle of acquaintances--a process which typically takes months or years. But there are exceptions: use of the Internet in the 1990s, for example, may have spread more rapidly than any other innovation in the history of humankind. Furthermore, the Internet is changing the very nature of diffusion by decreasing the importance of physical distance between people. The fifth edition addresses the spread of the Internet, and how it has transformed the way human beings communicate and adopt new ideas.

    Instead of giving you the most broadly popular result, Google now tries to predict what you are most likely to click on. According to MoveOn.org board president Eli Pariser, Google's change in policy is symptomatic of the most significant shift to take place on the Web in recent years - the rise of personalization. In this groundbreaking investigation of the new hidden Web, Pariser uncovers how this growing trend threatens to control how we consume and share information as a society-and reveals what we can do about it.Though the phenomenon has gone largely undetected until now, personalized filters are sweeping the Web, creating individual universes of information for each of us. Facebook - the primary news source for an increasing number of Americans - prioritizes the links it believes will appeal to you so that if you are a liberal, you can expect to see only progressive links. Even an old-media bastion like "The Washington Post" devotes the top of its home page to a news feed with the links your Facebook friends are sharing. Behind the scenes a burgeoning industry of data companies is tracking your personal information to sell to advertisers, from your political leanings to the color you painted your living room to the hiking boots you just browsed on Zappos.In a personalized world, we will increasingly be typed and fed only news that is pleasant, familiar, and confirms our beliefs - and because these filters are invisible, we won't know what is being hidden from us. Our past interests will determine what we are exposed to in the future, leaving less room for the unexpected encounters that spark creativity, innovation, and the democratic exchange of ideas.While we all worry that the Internet is eroding privacy or shrinking our attention spans, Pariser uncovers a more pernicious and far-reaching trend on the Internet and shows how we can - and must - change course. With vivid detail and remarkable scope, The Filter Bubble reveals how personalization undermines the Internet's original purpose as an open platform for the spread of ideas and could leave us all in an isolated, echoing world.

    Many scholars have argued that the social sciences rely too heavily on quantitative research and formal models and have attempted to develop and refine rigorous methods for using case studies. This text presents a comprehensive analysis of research methods using case studies and examines the place of case studies in social science methodology. It argues that case studies, statistical methods, and formal models are complementary rather than competitive. The book explains how to design case study research that will produce results useful to policymakers and emphasizes the importance of developing policy-relevant theories. It offers three major contributions to case study methodology: an emphasis on the importance of within-case analysis, a detailed discussion of process tracing, and development of the concept of typological theories. Case Studies and Theory Development in the Social Sciences will be particularly useful to graduate students and scholars in social science methodology and the philosophy of science, as well as to those designing new research projects, and will contribute greatly to the broader debate about scientific methods.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    H. Evergreen, Effective Data Visualization shows readers how to create Excel charts and graphs that best communicate data findings. This comprehensive how-to guide functions as a set of blueprints--supported by research and the author's extensive experience with clients in industries all over the world--for conveying data in an impactful way. Delivered in Evergreen's humorous and approachable style, the book covers the spectrum of graph types available beyond the default options, how to determine which one most appropriately fits specific data stories, and easy steps for making the chosen graph in Excel.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

    A six-step model offers invaluable assistance for selecting a topic, searching the literature, developing arguments, surveying the literature, critiquing the literature, and writing the literature review.

    This essential resource includes the most current information on theory, research, and practice at individual, interpersonal, and community and group levels. This edition includes substantial new content on current and emerging theories of health communication, e-health, culturally diverse communities, health promotion, the impact of stress, the importance of networks and community, social marketing, and evaluation.

    Replete with illustrative scenarios and topics for discussion and writing, this professional title provides the pedagogical overview that ESL/EFL teachers need to teach with Atlas, Go For It!, Listen In, and Expressions!

    A how-to guide to classroom inquiry that takes educators through the research process step by step, answering each critical question from where do I begin? through publishing the results.

    In this provocative new book, headline-making psychologist and social commentator Dr. Jean Twenge explores why the young people she calls "Generation Me" -- those born in the 1970s, 1980s, and 1990s -- are tolerant, confident, open-minded, and ambitious but also cynical, depressed, lonely, and anxious.Herself a member of Generation Me, Dr. Twenge uses findings from the largest intergenerational research study ever conducted -- with data from 1.3 million respondents spanning six decades -- to reveal how profoundly different today's young adults are. Here are the often shocking truths about this generation, including dramatic differences in sexual behavior, as well as controversial predictions about what the future holds for them and society as a whole. Her often humorous, eyebrow-raising stories about real people vividly bring to life the hopes and dreams, disappointments and challenges of Generation Me.GenMe has created a profound shift in the American character, changing what it means to be an individual in today's society. The collision of this generation's entitled self-focus and today's competitive marketplace will create one of the most daunting challenges of the new century. Engaging, controversial, prescriptive, funny, "Generation Me" will give Boomers new insight into their offspring, and help those in their teens, 20s, and 30s finally make sense of themselves and their goals and find their road to happiness.