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The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places (CSLI Lecture Notes S)
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- ISBN-101575860538
- ISBN-13978-1575860534
- PublisherCenter for the Study of Language and Inf
- Publication dateJanuary 29, 2003
- LanguageEnglish
- Dimensions6 x 1 x 9 inches
- Print length305 pages
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- Publisher : Center for the Study of Language and Inf (January 29, 2003)
- Language : English
- Paperback : 305 pages
- ISBN-10 : 1575860538
- ISBN-13 : 978-1575860534
- Item Weight : 1.02 pounds
- Dimensions : 6 x 1 x 9 inches
- Best Sellers Rank: #1,450,776 in Books (See Top 100 in Books)
- #237 in Cognitive Psychology (Books)
- #359 in Media Studies (Books)
- #1,534 in Sociology (Books)
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About the authors

Byron Reeves, Ph.D., is the Paul C. Edwards Professor in the Department of Communication at Stanford University, and currently serves Co-Director of the Stanford H-STAR Institute (Human Sciences and Technologies Advanced Research), a Stanford laboratory working at the intersection of computing and social sciences. He is also Founder and Faculty Director of the Stanford Media X Program that organizes research and knowledge transfer between industry and Stanford researchers working on information technology.
Byron is an expert on the psychological processing of media in the areas of attention, emotions, and physiological responses, and is co-author of The Media Equation: How People Respond to Computer, Television and New Media Like Real People and Places. He has published over 100 research papers about media psychology and his research has been the basis for a number of products at companies such as Microsoft, IBM, and Hewlett-Packard, in the areas of voice interfaces, automated dialogue systems, conversational agents, enterprise software and interaction design. He is currently working on applications of multi-player game technology to the conduct of serious work and is Co-Founder, with Leighton Read, of Seriosity, Inc.
Byron received his Ph.D. in Communication from Michigan State University, and his B.F.A. in Graphic Design and Journalism from Southern Methodist University. Prior to joining the faculty at Stanford in 1986, Byron was a professor for ten years in the School of Journalism & Mass Communication and Associate Director of the Mass Communication Research Center at the University of Wisconsin-Madison.

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The media equation is a good enough predictor of user behavior, at least for telephone-based spoken dialog systems of the form my company builds, that it has informed our designs from top to bottom. Our applications apologize if they make a mistake. Callers respond well to this. Sure, the callers know they're talking to a machine, but this doesn't stop them from saying "thank you" when it's done or "please" before a query or feeling bad (or angry) if the computer can't understand them. Another strategy recommended by Nass and Reeves that we follow is trying to draw the caller in to work as a team with the computer; again, Nass and Reeves support this with several clever experiments. There is also a useful section on flattery, looking at the result of the computer flattering itself and its users; it turns out that we rate computers that flatter themselves more highly than ones that are neutral.
Among other interesting explanations you get in this book are why we're more tolerant of bad pictures than bad sound, why we focus on moving objects, speaking rate equilibrium, what we can do to make someone remember an event in a video, and the role of gender.
This book is very quick and easy to read. I read it in two days while on vacation it was so fascinating. In contrast to the classical yet dry social science format of hypothesis, experimental methodology, results, and essentially a summary of the results as a conclusion, Nass and Reeves only vaguely summarize their experimental methodology and take a no-holds-barred approach to drawing conclusions. This may annoy social scientists, most of whom expect their own kind to be far more circumspect.
This book is an absolute must-read for anyone designing mediated interfaces. For those who don't believe the results, I'd suggest running some experiments; our company did, and it made us believers.
They have presupposed the "equation" they purport to have discovered, and designed their experiments to try and uncover it. This book chronicles the worst example I have ever seen of what happens when you set up a scientific experiment to try and show what you want to find, rather than to collect unbiased data and then scour the results and draw your conclusions after the fact.
Reeves and Nass expect to find the Media Equation beneath every stone, and consequently they do. The experiments themselves, to anyone with a background in legitimate science, are a casebook of poor design. They ignore intervening variables, intercoder reliability, and representative sampling. They lean heavily on self-selected and forced participants, subjectively worded and loaded questions, and performing statistical tests on non-numerical data (what is the mean of "rarely" and "often"...? Reeves and Nass will base their results on it).
In many cases, they contradict their own results from earlier points in the book, when it suits the experiment at hand. Other times, it seems they will ascribe every reaction to the media equation, regardless of how preposterous it seems. Case in point: People remember a face on a t.v. screen better when it is a close up than when it is a long distance shot. No kidding -- but Reeves and Nass chalk this up to a "social reaction" to the face. I know quite a few information theorists *and regular people on the street* who will tell you they remember a close-up better simply because there is more detail to see. Reeves and Nass don't even recognize the possibility.
But worst of all is the grandstanding, overhyped supergeneralization of the results. None of these so-called experiments has any external validity (many are not even internally consistent), yet the authors' claims extend into every field, in every walk of life. The Media Equation, they believe, is the root cause of just about everything.
This is Bad Science. At It's Worst.
In fact, this book is far from it. Well, as far from it as social science can get. In fact, is the most "scientific" of the user interface books I have read.
The main point I took away from the book is that people interact with objects, especially interactive and media devices, as if they were people. They demonstrate that when user interfaces are designed to be polite and interact in a positive social manner, the person has a much more enjoyable and profitable interaction.
Other books on the topic of user interface design are far less scientific, relying on generalizations and suppositions rather than constructing a study. Some use data from a usability evaluation, but these are often far from scientific.
The authors construct hypotheses, usually based on the results of studies of interaction between humans, and see if the results of the results hold true for human-machine interaction.
Usually, it does.






