The science & mathematics behind communication

From Arizona State University Libraries

From Arizona State University Libraries

Take a minute and let Anali tell you about some of the great features of EBSCOhost Academic Search™ Premier.

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Academic Search™ Premier is a great place to start your research for almost any subject. Academic Search Premier is a research database like a specialized search engine that provides fast access to the full text of over 8,450 journals when you need results now! You can also directly export your citations into your favorite bibliographic management software.

In 1975 Tefko Saracevic declared “the subject knowledge view” to be the most fundamental perspective of relevance. This paper examines the assumptions in different views of relevance, including “the system's view” and “the user's view” and offers a reinterpretation of these views. The paper finds that what was regarded as the most fundamental view by Saracevic in 1975 has not since been considered (with very few exceptions). Other views, which are based on less fruitful assumptions, have dominated the discourse on relevance in information retrieval and information science. Many authors have reexamined the concept of relevance in information science, but have neglected the subject knowledge view, hence basic theoretical assumptions seem not to have been properly addressed. It is as urgent now as it was in 1975 seriously to consider “the subject knowledge view” of relevance (which may also be termed “the epistemological view”). The concept of relevance, like other basic concepts, is influenced by overall approaches to information science, such as the cognitive view and the domain-analytic view. There is today a trend toward a social paradigm for information science. This paper offers an understanding of relevance from such a social point of view.

The life span of a Google query is less then 1/2 second, and involves quite a few steps before you see the most relevant results. Here's how it all works.

This orientation for students editing Wikipedia as a class assignment consists of four main modules:
Welcome, a short introduction;
The Core, an overview of Wikipedia's core principles;
Editing, a tutorial on the basic mechanics of editing pages and communicating with others; and
Advanced, some selected advanced topics to help you get off to a good start with your first article.
In total, the four modules should take about one hour to complete.

Learn how to use Google Scholar, your gateway to scholarly articles in peer-reviewed journals, patents, court opinions, etc.

In an effort to make Zotero as user friendly as possible we have developed these screencasts demonstrating many of the basic functions of Zotero. Click on any of the images to watch screencasts detailing the features named below. Special thanks to Steve Bailey from CU-Boulder for preparing the introductory demo.

This one-page quick reference helps you to remember the most frequently used wiki markup commands.

Evaluating Wikipedia article quality is a reference guide with specific steps you can take to get the most out of Wikipedia, as well as a look at how its quality system works.

A screencast introducing Wikipedia talk pages and how to use them. Script here, OpenOffice slideshow available upon request.

"Welcome to Wikipedia" gives you a basic introduction into contributing to Wikipedia. You will learn how to create a Wikipedia user account, how to start editing, and how to communicate with other contributors. You will also learn how articles evolve on Wikipedia and how to rate the quality of an existing article. The "Welcome to Wikipedia" brochure contains 17 pages and an additional quick reference that helps you to remember the most frequently used wiki markup commands.

This is a talk (ok, a long talk, ~30 minutes) about whether Google's Book Search project -- called "massive copyright infringement" by the American Association of Publishers, is "fair use"? It is.

There just isn’t such a thing as ‘‘copyright policy’’ anymore. Every modern copyright policy becomes Internet policy – policy that touches on every aspect of how we use the net. And as we make the transition from a world where everything we do includes an online component to a world where everything we do requires an online component, it’s becoming the case that there’s no such thing as ‘‘Internet policy’’ – there’s just policy.

The explicit, above-the-water-line paradigm of information science is well known and widely discussed. Every disciplinary paradigm, however, contains elements that are less conscious and explicit in the thinking of its practitioners. The purpose of this article is to elucidate key elements of the below-the-water-line portion of the information science paradigm. Particular emphasis is given to information science's role as a meta-science - conducting research and developing theory around the documentary products of other disciplines and activities. The mental activities of the professional practice of the field are seen to center around representation and organization of information rather than knowing information. It is argued that such representation engages fundamentally different talents and skills from those required in other professions and intellectual disciplines. Methodological approaches and values of information science are also considered.

Three meanings of information are distinguished: Information-as-process; information-as-knowledge; and information-as-thing, the attributive use of information to denote things regarded as informative. The nature and characteristics of information-as-thing are discussed, using an indirect approach (What things are informative?). Varieties of information-as-thing include data, text, documents, objects, and events. On this view information includes but extends beyond communication. Whatever information storage and retrieval systems store and retrieve is necessarily information-as-thing. These three meanings of information, along with information processing, offer a basis for classifying disparate information-related activities (e.g., rhetoric, bibliographic retrieval, statistical analysis) and, thereby, suggest a topography for information science.

Today I want to talk about categorization, and I want to convince you that a lot of what we think we know about categorization is wrong. In particular, I want to convince you that many of the ways we're attempting to apply categorization to the electronic world are actually a bad fit, because we've adopted habits of mind that are left over from earlier strategies.

by Tim O'Reilly This article is an attempt to clarify just what we mean by Web 2.0.

From Michael Wesch's Digital Ethnography blog My student-researchers and I tried something a little different to kick off our semester. Instead of the standard syllabus that requires everybody to read a few articles to discuss, we decided instead to organize ourselves into a Smart Mob that would try to read a good hunk of the literature on a single topic in one go. Each student was required to find 5 articles, read them, and summarize them; uploading their summaries (or the author’s own abstract) into a ZohoCreator form. ZohoCreator is a free service that allows you to create database input forms.

by Roy Tennant I no longer believe in the future of bibliographic control. I no longer believe that the term bibliographic encompasses the universe in which we should be interested, and I no longer think control is either achievable or even desirable. We have entered the age of descriptive enrichment and we'd better get bloody well good at it.

The Basic search help article covers all the most common issues, but sometimes you need a little bit more power. This document will highlight the more advanced features of Google Web Search. Have in mind though that even very advanced searchers, such as the members of the search group at Google, use these features less than 5% of the time. Basic simple search is often enough. As always, we use square brackets [ ] to denote queries, so [ to be or not to be ] is an example of a query; [ to be ] or [ not to be ] are two examples of queries.

I do a bit with so-called Semantic Web technologies (OK, I've written a couple of articles, have a book proposal in the works, and am about to start a job as a Semantic web researcher ... as I said, "a bit"), but I must confess to never really getting certain aspects of it. I like logic programming, and I'm certainly interested in knowledge representation, and I do a bunch of web stuff so I must be a Semantic Web person. However, some bit never clicked for me, some key shared assumption left me feeling a bit out of the flow of things. I used to characterize this as having more of a logician/philosopher background, but that didn't seem quite right. During the recent Google and SOAP furor, I had a little insight that led to the following prima facie argument for the Semantic Web. I hope it helps other people "get it".

The Web's structure has been studied at a global level, considering the network as a whole, and at a local level, studying focused neighborhoods and "community" structures. This analysis has revealed an intricate structure that suggests improved methods for organizing and accessing information and offers the opportunity to chart interests and relationships within society at an unprecedented level of detail.

In addition to providing easy access to billions of web pages, Google has many special features to help you to find exactly what you're looking for. Some of our most popular features are listed below.

Google Scholar provides a simple way to broadly search for scholarly literature. From one place, you can search across many disciplines and sources: peer-reviewed papers, theses, books, abstracts and articles, from academic publishers, professional societies, preprint repositories, universities and other scholarly organizations. Google Scholar helps you identify the most relevant research across the world of scholarly research.

The fundamental principles by which Wikipedia operates are summarized in the form of five "pillars"

Encyclopædia Britannica, Inc. (2006). Fatally Flawed: Refuting the recent study on encyclopedic accuracy by the journal Nature.

And not only can we collect that data, we can analyze it as well, looking for patterns, information that might help us change both the quality and the length of our lives. We can live longer and better by applying, on a personal scale, the same quantitative mindset that powers Google and medical research. Call it Living by Numbers—the ability to gather and analyze data about yourself, setting up a feedback loop that we can use to upgrade our lives, from better health to better habits to better performance.

Section 1. All legislative powers herein granted shall be vested in a Congress of the United States, which shall consist of a Senate and House of Representatives.

Metadata, literally "data about data," has become a widely used yet still frequently underspecified term that is understood in different ways by the diverse professional communities that design, create, describe, preserve, and use information systems and resources. It is a construct that has been around for as long as humans have been organizing information, albeit transparently in many cases, and today we create and interact with it in increasingly digital ways. For the past hundred years at least, the creation and management of metadata has primarily been the responsibility of information professionals engaged in cataloging, classification, and indexing; but as information resources are increasingly put online by the general public, metadata considerations are no longer solely the province of information professionals.

Numbers are making their way into the smallest crevices of our lives. We have pedometers in the soles of our shoes and phones that can post our location as we move around town. We can tweet what we eat into a database and subscribe to Web services that track our finances. There are sites and programs for monitoring mood, pain, blood sugar, blood pressure, heart rate, cognitive alacrity, menstruation, and prayers. Even sleep—a challenge to self-track, obviously, since you're unconscious—is yielding to the skill of the widget maker. With an accelerometer and some decent algorithms, you will soon be able to record your sleep patterns with technology that costs less than $100.

Wikipedia article

These standards were reviewed by the ACRL Standards Committee and approved by the Board of Directors of the Association of College and Research Libraries (ACRL) on January 18, 2000, at the Midwinter Meeting of the American Library Association in San Antonio, Texas. These standards were also endorsed by the American Association for Higher Education (October 1999) and the Council of Independent Colleges (February 2004).

We find that the average of d over all pairs of vertices is =0.35+2.06log(N) (Fig. 1c), indicating that the web forms a small-world network, which characterizes social or biological systems. For N=8*10^8, =18.59; that is, two randomly chosen documents on the web are on average 19 clicks away from each other.

The term "search engine" is often used generically to describe both crawler-based search engines and human-powered directories. These two types of search engines gather their listings in radically different ways.

So, how do crawler-based search engines go about determining relevancy, when confronted with hundreds of millions of web pages to sort through? They follow a set of rules, known as an algorithm. Exactly how a particular search engine's algorithm works is a closely-kept trade secret. However, all major search engines follow the general rules below.

Giles, J. (2005). Internet encyclopaedias go head to head. Nature, 438(7070), 900-901. The exercise revealed numerous errors in both encyclopaedias, but among 42 entries tested, the difference in accuracy was not particularly great: the average science entry in Wikipedia contained around four inaccuracies; Britannica, about three.

The life span of a Google query normally lasts less than half a second, yet involves a number of different steps that must be completed before results can be delivered to a person seeking information.

Some thirty years ago, the RAND Corporation, America's foremost Cold War think-tank, faced a strange strategic problem. How could the US authorities successfully communicate after a nuclear war?

Most of the time you'll find exactly what you were looking for with just a basic query. However the following tips can help you refine your technique to make the most of your searches. Throughout the article, we'll use square brackets [ ] to signal queries, so [ black and white ] is one query, while [ black ] and [ white ] are two.

The recent development of various methods of modulation such as PCM and PPM which exchange bandwidth for signal-to-noise ratio has intensified the interest in a general theory of communication. A basis for such a theory is contained in the important papers of Nyquist1 and Hartley2 on this subject. In the present paper we will extend the theory to include a number of new factors, in particular the effect of noise in the channel, and the savings possible due to the statistical structure of the original message and due to the nature of the final destination of the information.

This paper is written in three main sections. In the first and third, W. W. is responsible both for the ideas and the form. The middle section, namely “2), Communication Problems of Level A” is an interpreta- tion of mathematical papers by Dr. Claude E. Shannon of the Bell Telephone Laboratories. Dr. Shan- non’s work roots back, as von Neumann has pointed out, to Boltzmann’s observation, in some of his work on statistical physics (1894), that entropy is related to “missing information,” inasmuch as it is related to the number of alternatives which remain possible to a physical system after all the macroscop- ically observable information concerning it has been recorded. L. Szilard (Zsch. f. Phys. Vol. 53, 1925) extended this idea to a general discussion of information in physics, and von Neumann (Math. Foun- dation of Quantum Mechanics, Berlin, 1932, Chap. V) treated information in quantum mechanics and particle physics.

from Search Engine Showdown Measuring the size of the constantly changing Web search engine databases is a complex task. The following Size Showdowns are based on the hits from actual search results. See also Why size matters. Size statistics last updated Dec. 31, 2002.

The rapid adoption of social network sites by teenagers in the United States and in many other countries around the world raises some important questions. Why do teenagers flock to these sites? What are they expressing on them? How do these sites fit into their lives? What are they learning from their participation? Are these online activities like face-to-face friendships – or are they different, or complementary? The goal of this chapter is to address these questions, and explore their implications for youth identities. While particular systems may come and go, how youth engage through social network sites today provides long-lasting insights into identity formation, status negotiation, and peer-to-peer sociality.

Searching on the Internet today can be compared to dragging a net across the surface of the ocean. While a great deal may be caught in the net, there is still a wealth of information that is deep, and therefore, missed. The reason is simple: Most of the Web's information is buried far down on dynamically generated sites, and standard search engines never find it.

James Surowiecki explores a deceptively simple idea that has profound implications: large groups of people are smarter than an elite few, no matter how brilliant—better at solving problems, fostering innovation, coming to wise decisions, even predicting the future. This seemingly counterintuitive notion has endless and major ramifications for how businesses operate, how knowledge is advanced, how economies are (or should be) organized and how we live our daily lives.

Google. Wikipedia. Threadless. All are well-known examples of large, loosely organized groups of people working together electronically in surprisingly effective ways. These new modes of organizing work have been described with a variety of terms—radical decentralization, crowd-sourcing, wisdom of crowds, peer production, and wikinomics.1 The phrase we find most useful is collective intelligence, defined very broadly as groups of individuals doing things collectively that seem intelligent.

The purposes of this study were to explore college students' perceptions, uses of, and motivations for using Wikipedia, and to understand their information behavior concerning Wikipedia based on social cognitive theory (SCT). Approximately one-third of the students reported using Wikipedia for academic purposes. The students tended to use Wikipedia for quickly checking facts and finding background information. They had positive past experiences with Wikipedia; however, interestingly, their perceptions of its information quality were not correspondingly high. Respondents' past experience with Wikipedia, their positive emotional state, their disposition to believe information in Wikipedia, and information utility were positively related to their outcome expectations of Wikipedia. However, among the factors affecting outcome expectations, only information utility and respondents' positive emotions toward Wikipedia were related to their use of it.

What does a person need to know today to be a full-fledged, competent and literate member of the information society? As we witness not only the saturation of our daily lives with information organized and transmitted via information technology, but the way in which public issues and social life increasingly are affected by information-technology issues - from intellectual property to privacy and the structure of work to entertainment, art and fantasy life - the issue of what it means to be information-literate becomes more acute for our whole society. Should everyone take a course in creating a Web page, computer programming, TCP/IP protocols or multimedia authoring? Or are we looking at a broader and deeper challenge - to rethink our entire educational curriculum in terms of information?

In this first video of his critical thinking series, Howard introduces 5 key Internet literacies: attention, participation, cooperation, crap detection, and network awareness and discusses how mastering critical thinking skills can keep children safer online.

Roman, Steven. (2003). Access Database Design & Programming, 2nd ed. Sebastopol, CA: O'Reilly.

What is RSS? RSS is a Web content syndication format. Its name is an acronym for Really Simple Syndication. RSS is a dialect of XML. All RSS files must conform to the XML 1.0 specification, as published on the World Wide Web Consortium (W3C) website.

In this second part of his critical thinking series, Howard discusses how new online tools, personal trust networks and search skills can create a society prepared to distinguish between good and bad information.

As a company, Google focuses on three key areas: Search, Ads and Apps. Search is our core technology; ads are our central business proposition; and apps are the umbrella over our web-based software that you can access anywhere, any time. While each of these has a lot of technology under the hood, the basic tenets for Search, Ads and Apps are very simple. We've created some short videos explaining the principles behind our core services. For more information or to share your thoughts, visit our Help Forum.

Professor Eric Faden of Bucknell University created this humorous, yet informative, review of copyright principles delivered through the words of the very folks we can thank for nearly endless copyright terms.

This site is designed to help you learn how to conduct research using the library's resources. Click the Start button to begin or select the icons below to jump to a specific section.

In the third part of his critical thinking series, Howard covers how teachers can turn students into "online detectives" by teaching critical research skills to determine site ownership and bias. Also, he describes some of his own collaborative teaching techniques.

Building on the examination of relevance in the preceding (1976) re- view, this (2006) work updates the travails of relevance in information sci- ence for the past 30 years or so. Relevance still remains a basic notion in information science, and particularly in information retrieval (IR). The aim of this work is still substantially the same: it is an attempt to trace the evolution of thinking on relevance in information science for the past three decades and to provide an updated, contemporary framework within which the still widely dissonant ideas on relevance might be interpreted and related to one another.

An application programming interface (API) is an interface implemented by a software program that enables it to interact with other software. It facilitates interaction between different software programs similar to the way the user interface facilitates interaction between humans and computers.

Although some analysts previously questioned the finding of search dominance, it's a user behavior that gets stronger every year. Today, many users are so reliant on search that it's undermining their problem-solving abilities. Ironically, the better search gets, the more dangerous it gets as people increasingly assume that whatever the search engine coughs up must be the answer.

The answer to almost any question is available within seconds, courtesy of the invention that has altered how we discover knowledge - the search engine. Materializing answers from the air turns out to be the easy part - the part a machine can do. The real difficulty kicks in when you click down into your search results. At that point, it's up to you to sort the accurate bits from the misinfo, disinfo, spam, scams, urban legends, and hoaxes. "Crap detection," as Hemingway called it half a century ago, is more important than ever before, now that the automation of crapcasting has generated its own word: "spamming."

This section discusses how to do basic EndNote tasks. To get started with EndNote, we will open an EndNote library and look at its components. Then we will discuss how to modify the display of the library, find and view references, change EndNote preferences, and conclude your EndNote session.

This section discusses the process of creating an EndNote library and populating it with references. (For information about the basics of working with existing EndNote libraries, see the Getting Started section.)

When you think about “information,” what probably comes to mind are streams of words and numbers. Google’s pretty good at organizing these types of information, but consider all the things you can’t express with words: what does it look like in the middle of a sandstorm? What are some great examples of Art Nouveau architecture? Should I consider wedding cupcakes instead of a traditional cake? This is why we built Google Images in 2001. We realized that for many searches, the best answer wasn’t text—it was an image or a set of images. The service has grown quite a bit since then. In 2001, we indexed around 250 million images. By 2005, we had indexed over 1 billion. And today, we have an index of over 10 billion images.