The Librarian Guide to Cognitive Bias

Over the past week, I’ve written up posts examining different cognitive biases. I’ve reviewed the academic research on each of them and provided specific ideas on how you can overcome these problems. In this post, I bring it all together and help you read through the series. Feel free to comment here or on any fo the individual posts. Did I leave out an important bias? (I’m sure I did, but I wanted to look at five to get things started).

• Part 1: Confirmation Bias
• Part 2: Availability heuristic
• Part 3: Fundamental attribution error
• Part 4: Selection bias
• Part 5: Anchoring

I wrote this series from the perspective of a librarian and looking at how people understand information. I hope that non-librarians also find it to be of interest. If you’re doing anything in life beyond digging ditches, you’re probably working with information constantly so it is worth your while to think through how you think.

The Librarian Guide to Cognitive Bias: Anchoring

Sometimes you just get fixed on an idea.

I first encountered the idea of anchoring in my reading of economics, especially that exciting sub-field that combines psychology and economics (sometimes called behavioural economics). Anchoring can be defined as just getting fixated on a single idea, even if other options are better for you. As with other important cognitive biases, it was first thought up by Daniel Kahneman and Amos Tversky several decades ago but it is one of those ideas that takes some time to understand. It stikes me as similar to the halo effect; the bias where if you think positively about a person in general, you’ll tend to view all aspects of that person positively even if it is not warranted. Anchoring, like the other cognitive biases discussed in this series, is all about taking shortcuts and trying to save thinking time. Unlike the other biases discussed though, anchoring most likely leads to problems; I struggle to see any benefit from allowing anchoring to happen. If you think that anchoring can be truly worthwhile, then I’d welcome you to comment and share your view.

The Research on Anchoring

Happily, there are plenty of studies concerning anchoring covering everything from information behaviour, to real estate to business. In a 2007 article, Annie Lau and Enrico Coiera found that anchoring has effects in searching for information; it limits what you can find. As they state in their abstract, “A person’s prior belief (anchoring) has a significant impact on their post-search answer.” Their research also confirms a bit of folk search engine wisdom; if a document or item is listed early in the search results, it is more likely to be used. I’ve actually encountered quite a few occasions where the top results have very little value. So, it pays to scan through at least a few dozen search results rather than just look at the first handful.

Anchoring also exerts an influence in the world of charities and donations. Two economists, Richard Martin and John Randal, experimented with a donation box at an art museum where admission was free. They wanted to see if different kinds of information – e.g. showing only large denomination bills in the box versus coins or small denomination notes – influenced the donation behaviour. It looks like it did. That also explains why most fundraisers suggest amounts ($50, $100 or more) and partly explains why I ignore those people standing on the street trying to raise funds. The options you present to people have an anchoring effect to encourage people to choose an option that is listed. It reminds me of the fact that some coffee shops provide small coffees but don’t list it on the menu, you can only get it by request. I may be taking some liberties with the research but I think it all makes sense.

Set sail and overcome anchoring

Overcoming anchoring and setting sail into better thinking (ha, I’m enjoying the nautical metaphors too much clearly) is a tricky since anchoring can be quite subtle. Here are some strategies that could help you overcome this cognitive bias and think better.

• Ask for other options: You’re give three options and none of them appeal to you; ask for some other options.
• Deconstruct it!: Think about the case of donations to the art museum above; how is your thinking and approach being shaped? Do you accept how it is being shaped?
• Anchor yourself: Ramit Sehti, the personal finance/entrepreneurship author, is a big fan of using psychology to constrain yourself and make better choices. Can you find a way to use anchoring to make better decisions? Maybe change your default search engine for a few days and see what happens?

References:

Ariely, Dan. Predictably Irrational. You can get the book and blog that really started me thinking about this whole topic.

Martin, Richard and Randal, John. How is donation behaviour affected by the donations of others?. Journal of Economic Behavior & Organization, 2008

Lau, Annie YS and Coiera, Enrico W. “Do People Experience Cognitive Biases while Searching for Information?“, Journal of the American Medical Informatics Association, 2007

More than two dozen great papers on cognitive biases can be read (and quite a few read for free!) on Dan Ariely’s list of academic papers.

The Librarian Guide to Cognitive Bias: Selection Bias

Selection Bias: Or, Yes, Johnny, it really is difficult to get a properly random and representative sample

Selection bias is a very well known problem in social science research and it is something that comes up all the time. You might even say that it has become a cliche to critique an article by raising the problem of selection bias. I recall studying the problem in graduate school and finding it absolutely fascinating. It is particularly problematic when one is aiming to sample a population; for instance, if you sample the population of Canada by looking in the phone book, you will get a poor result since you will be missing quite a few people including people who use cell phones exclusively or who choose to have their phone numbers unlisted. This is where cutting corners in research and preparation can cause significant problems.

Since this problem is so well known and understood in research circles, I am not going to review the literature as I have previously. One very common problem that afflicts much psychological research is its dependence on students as participants; do you think focusing on mostly young, mostly privileged people is likely to yield substantial insights into human nature? I doubt it. Selection bias has also been identified as a problem for researchers who rely on the news media for evidence. There is also plenty of cases of this being identified as a problem in medical studies, accounting and other social policy. Even experts in statistical research can commit this error and that’s partly due to the fact that you can’t eliminate this problem with pure math. You actually need to know something about the world.

You might be skeptical about this bias and say, “Well, I don’t do any statistical analysis in my work so this doesn’t matter.” I have a bit of a love and hate relationship with statistics myself, so I see where you’re coming from. Even if you don’t produce statistical research in your work, you can’t escape from it. Do you ever read about studies and make decisions based on them? Do you ever need to know that attitude of your customers or co-workers and don’t have the resources to ask everybody? What about asking for advice? Do you only ask your friends or do you ask critics too? Then you need to understand something about the selection bias. Understanding the selection bias doesn’t guarantee perfect quality research, but it will get you a long way toward producing better decisions and help you critically make sense of statistical data.

How to cope with selection bias

In this post, I’m going to deviate from the earlier posts in the series and ask for you to comment. If you’d like to share a story about how selection bias has affected your decisions or thinking about the world, that would be interesting too. Choose any of the following and complete the sentence in a comment:

• To avoid selection bias in work, I could…

• To cope with selection bias in my research project, I plan to…

• To minimize selection bias in my personal decision making, I will…

What is the role for the librarian to cope with this kind of problem? One option might be to serve as a sounding board for a subject matter expert who is so deeply involved in a project that miss things that will be obvious to a civilian. Conducting a literature review – either full out scientific or something more modest – can be helpful. Honest writers will share how selection bias may have affected their work.

The fifth and final post in this series will explore the concept of anchoring. Come back soon to find it posted here.

The Librarian Guide to Cognitive Bias: Fundamental Attribution Error

When we are trying to understand and explain what happens in social settings, we tend to view behavior as a particularly significant factor. We then tend to explain behavior in terms of internal disposition, such as personality traits, abilities, motives, etc. as opposed to external situational factors.
- Changing Minds definition of Fundamental Attribution Error

In contrast with the other cognitive biases discussed here, fundamental attribution error (FAE) is more controversial than the others. I get the impression that it is is regarded as less robust than other concepts explored in this series. However, I have seen examples of this in action often enough to consider it worthy of further exploration. This bias is also more concerned with perception and behaviour rather than information use per se. Given that librarians work with people all day though, understanding perception is important. If you need more convincing of the importance of understanding perception, then I’ll refer you to the SLA Alignment Project. Without further ado, let’s get into this error and see what can be done about it.

Explaining behaviour: the balance between personality and context

I’ve been thinking about this error for some time and have found it more difficult to explain than some of the other biases explored in this serires. Here’s the explanation I’ve come up with: fundamental attribution error occurs when you explain behaviour by personality primarily, rather than balancing it with context. Imagine you are told a story about a person who killed another person and nothing else; you might explain that by saying the person is evil. But maybe there is a context – the person was a soldier in a war – that better explains the behaviour. It is a question of focus and many people find it difficult to get the context right. As seen in the other parts of the series, fundamental attribution error saves mental effort at the expense of accuracy.

The Research on Fundamental Attribution Error

As with the availability heuristic, fundamental attribution error was discovered during psychological research in the 1970s. In a 1977 article that has been cited over two thousand times according to Google Scholar, Lee Ross found that participants in an experiment tend to overemphasize personality and character over context. It was based on an experiment where students were given pro-Castro and anti-Castro essays to read. As Wikipedia summarizes the experiment (conducted in 1967;  replicating this experiment in 2010 would require some modification):

Subjects read pro- and anti-Fidel Castro essays. Subjects were asked to rate the pro-Castro attitudes of the writers. When the subjects believed that the writers freely chose the positions they took (for or against Castro), they naturally rated the people who spoke in favor of Castro as having a more positive attitude toward Castro. However, contradicting Jones and Harris’ initial hypothesis, when the subjects were told that the writer’s positions were determined by a coin toss, they still rated writers who spoke in favor of Castro as having, on average, a more positive attitude towards Castro than those who spoke against him. In other words, the subjects were unable to see the influence of the situational constraints placed upon the writers; they could not refrain from attributing sincere belief to the writers.

The controversy on FAE is considerable however. John Sabni, Michael Siepmann and Julia Stein argue in a 2001 article that FAE, as conjectured by most social psychologists does not exist. They posit an alternative explanation that suggests that people are actually more motivated to save face or avoid embarrassment. Other psychologists have argued that encouraging students to focus on situations rather than personality may help in better understanding situations like the Jonestown. In the commercial context, I found it very interesting to see some research into the possibility that FAE may be taken into account when designing customer services. The controversy also concerns whether this phenomenon should be better termed as “correspondence bias” but I leave that particular debate to others.

As somebody who formerly worked in technical support, I can appreciate that. Some staff were tempted to label customers as incompetent, rather than considering other factors (e.g. the fact they be using a new operating system, that they are trying to do something new under stress etc). In some cases, there may have been a combination of situational pressure and lack of skill but I would apply FAE and come up with this: focus on things you can improve or adjust for the customer rather than compounding their frustration by labelling them as incapable or defective in some other way.

Practical Steps to Overcome Fundamental Attribution Error

• Avoid the evil/incompetent explanation: explaining behaviour by labelling somebody as evil or incompetent doesn’t advance things very far. You’ve insulted the person and then what do you do?
• Scan the environment: what are the constraints, rules and stresses affecting this person? Is their context different from yours? How?
• What would you do?: Imagine yourself performing the same action; why would you do it?

I don’t want to discount the importance of character and personality; that certainly matters.  I want you to consider other explanations and how ways to explain behaviour. Done well, this can help you understand people better. With any luck, it will help you be more productive in dealing with people. Does knowing about fundamental attribution error change how you approach things? For me, it helps me more calmly approach customer service phone  interactions and other bureaucratic situations.

References:

Ross, L. The intuitive psychologist and his shortcomings: Distortions in the attribution process. (1977) – I couldn’t locate a good reference link for this but it has appeared in a journal and in books.
Riggio, Heidi R and Garcia, Amber L. “The Power of Situations: Jonestown and the Fundamental Attribution Error.” Teaching of Psychology, 2009
Sabini, John; Siepmann, Michael and Julia Stein. “The Really Fundamental Attribution Error in Social Psychological Research.” Psychological Inquiry, 2001
Gebauer, Heiko; Krempl, Regine and Fleisch, Elgar. Exploring the Effect of Cognitive Biases on Customer Support Services, Creativity and Innovation Management, 2008

The Librarian Guide to Cognitive Bias: Availability heuristic

“If you can think of it, it must be important.”

- Esgate, A. & Groome, D. (2004). An Introduction to Applied Cognitive Psychology, definition of the availability heuristic

The availability heuristic is a major concern for librarians, especially those that find they need to convince their clients, patrons or members to use their services. In order to save time, many people will simply focus on information that occurs to them rather than attempting to research something from scratch. In fact, this is a novel way to look at the idea of experience in the workplace. Experience allows you to simply remember how you approached a problem rather than going through the steps of hatching a new solution. If the problems are actually very similar or the result is not very important, then the availability heuristic may not be such a bad thing. However, most professionals are not solving the exact same problems over and over again. Unfortunately, many will still rely on their experience and habits to solve problems rather than conducting research. That is an opportunity for librarians to make a contribution; notice the information habits of your users and then figure out where routines might be changed.

The Research on the Availability Heuristic

The availability heuristic was first discussed in a 1973 article (see references) by two psychologists, Amos Tversky and Daniel Kahneman. Their discussion explored memory and how experiment participants performed in experiments. I found the article itself to be rather technical, but you have to start somewhere. They do raise some interesting points such as the problem of people remembering and weighting vivid events more than mundane events (e.g. the fact that your flight was delayed once for four hours rather than the dozens or hundreds of times it all went smoothly). This original article and a much more recent article in the British Medical Journal (see references) explore how this bias can undermine the quality of physician decision making. The principle can be found in other contexts, not just life or death situations, such as business and banking.

The availability heuristic is known to be a problem in business and economics research, especially when it comes to risk, the availability heuristic has been noted as a problem. Given that a through understanding of risk is vital for banking and insurance, it is important to see how this bias could affect decisions there. This article – A Cognitive Theory of the Firm – apply the concept in novel ways. Bart Nooteboom makes the argument that the availability heuristic may explain the appeal of immediate gratification over greater long term benefit; immediate gratification is more accessible. The general idea is that people will, by default, go for the option that they remember best or that seems more vivid than other options even if it is far from the best option. The bias has also been called upon to explain the subprime mortgage collapse which was a major cause of the recent recession. Steven Schwarcz in his article, “Protecting Financial Markets: Lessons from the Subprime Mortgage Meltdown,” suggests that mortgage brokers, investors and others fell victim to the availability heuristic in only looking at recent changes in housing prices (e.g. 1990-2000) rather than longer term trends showing that housing prices do not always increase.

Practical Steps to Overcome the Availability Heuristic

• Look for the Mundane Counter-Example: Are you being overly focusing on dramatic cases rather than common cases?
• Call in a librarian: Yes, that’s a bit self-serving, but it can be difficult to get perspective sometimes and how better to help you with that than a professional with research expertise?
• Ask yourself, “Why did I think of this?”: Before acting on memory, consider why it came to mind. Are you remembering something that was merely a recent example or perhaps an example that is particularly emotionally vivid? There may be nothing wrong with that but consider it.

So what do you think? How can librarians help others overcome this bias? Many people may default to Google when searching for information even if it is far from comprehensive and can be manipulated. Demonstrating how the limits of these tools and perhaps referencing the availability heuristic may help you make your case that they should use your services or help you understand your users better.

References:

Behavioural Finance, Availability Heuristic (good basic definition here and references to major articles discussing the problem)

Kahneman, Daniel and Tversky, Amos. “Availability: A heuristic for judging frequency and probability.” Cognitive Psychology (1973)

Klein, Jill G . “Five pitfalls in decisions about diagnosis and prescribing.” British Medical Journal (2005)

Nooteboom, Bart  “A Cognitive Theory of the Firm,” 2002 (a paper)

Schwarcz, Steven L. “Protecting Financial Markets: Lessons from the Subprime Mortgage Meltdown.” American Law & Economics Association Annual Meetings (2008)

The Librarian Guide to Cognitive Bias: Confirmation Bias

“If one were to attempt to identify a single problematic aspect of human reasoning that deserves attention above all others, the confirmation bias would have to be among the candidates for consideration.”          – Raymond S. Nickerson, Department of Psychology, Tufts University

I don’t know about you but I like to think that I’m rational and think well. In most circumstances, that’s true but some recent insights from psychological research show that there are many weaknesses that undermine the rationality of human thinking. In this five part series, I’ll be exploring five concepts that affect how people think and process information: confirmation bias, availability heuristic, fundamental attribution error, selection bias, and anchoring. I came across some of these concepts back in grad school but others I’ve picked up in reading books and articles, especially those concerning behavioral economics. In reading through these posts, I hope you’ll join me in thinking through these challenges and beginning efforts to overcome them.

Confirmation bias: a long established principle in psychology research

Confirmation bias can be viewed as a type of information behaviour; it describes the tendency of people to seek out information that confirms what they already think or believe. In politics, that could mean only reading newspapers and writers that voice your opinions. In academic research, it might mean conducting a less through complete literature review lest one find articles that contradict one’s findings. To put it more generally, I’ll quote from Raymond Nickerson author of a 1998 academic article on the topic (see references below):

Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand….

Nickerson’s lengthy article cites over a hundred other studies exploring this concept further but it is reasonable to summarize the article as demonstrating that this is a real phenomenon (though Nickerson poses the question of whether it is always a problem). Depending on your context, bowing to confirmation bias may seem like a good idea if your goal is getting along rather than getting it right. In a professional context, that is a recipe for errors and mistakes.  The confirmation bias is also faster – indeed, cognitive biases are also known as cognitive shortcuts – than fully thinking through the problem. The more important a problem or question becomes, the more important it becomes to overcome this bias and really stretch ourselves. Imagine having a meeting to discuss which project proposals should be authorized only to have the chair of the committee express a view with nobody contradicting it. The desire to seek out consensus can limit our ability to actually think through problems and seek out other possibilities.

Practical Steps To Overcome Confirmation Bias

• Seek disconfirmation: What evidence could prove this wrong?
• Play the Devil’s Advocate: Give me somebody in the group permission to contract and question others. Such questioning should be informed by evidence.
• Slow down: Confirmation bias is more likely if you are rushed, so try to approach the question in a slower way.

There has also been some research (see below) in how specific professionals can overcome the bias and the effects it can have on the quality of decisions. After all, that is ultimately why this bias is important; it can lead to poor quality decisions.

References:

Arunachalam, Vairam and Wheeler, Patrick R. “The Effects of Decision Aid Design on the Information Search Strategies and Confirmation Bias of Tax Professionals.” Behavioral Research In Accounting, 2008

Jones, Martin and Sugden, Robert. “Positive confirmation bias in the acquisition of information.” Theory and Decision, 2001

Nickerson, Raymond. “Confirmation bias: A ubiquitous phenomenon in many guises.” Review of General Psychology, 1998

Parmley, Meagan Carleton. “The effects of the confirmation bias on diagnostic decision making.“  Phd Thesis, Drexel University, 2006

Shefri, Hersh. “How Psychological Pitfalls Generated the Global Financial Crisis,” May 2009 (Note: confirmation bias is one factor of several considered in this paper)

The Catalogue is Dead, Long Live the Catalogue, Part 5

The conclusion of my series exploring catalogue developments will look at open source tools and catalogue hacks. This fifth and final post in this series about the library catalogue admits that these tools are complex and difficult to redesign. Some of the ideas that I have discussed earlier in the series such as faceted search and visual search would likely require a major upgrade to new software, no easy task by any means. I have been told by academic librarians that upgrading a catalogue (and the ILS that goes with it) can easily take a year or more. Beyond upgrading the catalogue itself, what can users do to make catalogues more useful to them? I have three ideas: learn to use advanced search like a rock star, experiment with LibX and consider Social OPAC.

Using advanced search options may not seem like the traditional idea of hacking; you’re not modifying the technology for your own ends (my preferred, ‘classical’ definition of hacking) nor are you using technology to commit some sort of crime (the other definition of hacking). That said, I think you are hacking expectations of how people typically search. The power of advanced search can vary quite a lot; it is instructive to contrast Google with something like Factiva. Constructing a good search can take a bit longer at the beginning but I cannot recommend it enough. Instruction in searching is a traditional strength of librarians and it is something that we can continue to do.

Some weeks ago, I learned more about LibX – the browser plugin for libraries – and this is a great idea that I would like to see more of. LibX represents an alternative way to improve the user experience of search. Rather than coming at the problem from the server side and the ILS, LibX changes the experience from the user’s end through the installation of a browser plug-in. LibX has several good features to recommend it, but I would focus on two that are best likely to be understood by users: Support for xISBN and Support for Google Scholar. Say you have LibX installed and you’re checking out the latest releases on Amazon. LibX will read the ISBNs of books and turn them into a link to the institution’s catalogue. Likewise, if you are looking for academic articles using Google Scholar, LibX connects you from a citation you find in GS directly into the journal or database where the article can be read in full text. This makes the user experience of locating materials less complicated, with fewer steps.

I will close this post and my series on the catalogue with The Social OPAC. The creators of the Social OPAC describe it as, “an open source social discovery platform for bibliographic data.” As I understand it, the software stands between the user and the catalogue. Interesting features include support for SMS (i.e. you look up a book and instead of having to scribble a note on scrap paper, you just send the relevant information in a text a message to your cell phone), “RSS everything” (potentially, this could be a could way for people to stay informed about works by authors of interest or subjects) and a “Recommendation engine.” I am not sure how the recommendation engine in Social OPAC is powered but I very much like the idea of this. To see the Social OPAC in action, have a look at the Palos Verdes Library District in California. When one does a search there, faceted search is integrated on the left side (“Refine Your Search”) while there are tags on the right side. It looks like the tags are not specific to a given search though, which makes them a bit less useful in my view.

Thanks for reading this series. I have found it interesting to look at some of the major developments in catalogues and searching. As the title of the series suggests, I think the catalogue is going through a transition and that it can only become better.

Read the rest of the series:

The Catalogue is Dead, Long Live the Catalogue, Part 1

The Catalogue is Dead, Long Live the Catalogue, Part 2 (Faceted Search)

The Catalogue is Dead, Long Live the Catalogue, Part 3 (Visual Search)

The Catalogue is Dead, Long Live The Catalogue: Part 4 (Ideas for New Features)

The Catalogue is Dead, Long Live The Catalogue, Part 4

In today’s post, I will consider several features that I would like to see in library catalogues. For purposes of this post, I am thinking free form as in how would the catalogue look if we could build whatever we wish. In reality, I am aware that catalogues (and the related infrastructure) is a complex tool that is very difficult to upgrade in many cases. Several of these ideas are obviously inspired by Amazon, the major retailer of books and many more things. The fundamental presumption underlying these ideas is that catalogues can gain from involving their users further.

Reviews are often helpful in deciding whether or not to buy something – whether that buying involves time, money or something else. In using reviews, there are at least two models in integrating reviews in catalogue entries: reusing previously published reviews (from journals, newspapers etc) generally few in number or a high volume of user submitted reviews which can vary widely in quality. I like both for different reasons. Based on catalogues I have looked at, selecting a handful of quality reviews from publications appears to be the favoured approach. Such reviews are safe and often quite insightful. The case can be made for using user submitted reviews especially if these are limited by community. If I know that users like me found something useful, then would be great. The format of the reviews could have written comments, a star rating system and then some additional meta-data (e.g. for non-fiction, indicate level of background you think is needed).

Building on reviews is another idea that would be great to see in catalogues; what has my fellow academic/student/co-worker found of interest in the catalogue? This recalls a research technique I was taught as an undergraduate; “mining the bibliography.” Once one found a good book (or article), one then mined the bibliography for further sources. There is still great value to this method, but what about extending it to the catalogue. A user could enter all the usual search criteria (title, subject etc) and then have a social option (“show me all the catalogue records examined by graduate students in health sciences”). In this context, the Library is facilitating community between people of like interests. Implementing a system like this would require sophisticated infrastructure; detailed profiles on users and their habits (make this opt-in and protect it with a robust privacy policy) and a powerful database. The idea needs some further development but it is something I would like to see in use.

The final idea I have in mind is inspired by Flikr and Library Thing, two social cataloguing services that thrive on organic taxonomies generated by the user. From my own use, I like the Library Thing model best as it combines formal cataloguing (both Dewey Decimal and LC) with user generated tags; have a look at the Library Thing tag cloud. I have used the service and found it interesting. With over 800,000 members, there is certainly evidence to show that people like to catalogue and share their views with others. LT is also noteworthy for its achievements in building communities around reading; various authors (mainly fiction) have a presence in LT, there are free books for review and more. Such successes in engaging readers is something that librarians ought to take an interest in.

The question for today’s post is whether or not the social proposal advanced here is legitimate. It would represent a substantial change in the way that catalogues operate and the experience it provides. From a certain standpoint, this might appear a deviation from the purity of the catalogue as traditionally presented. I think such a change is due and that it has the potential to raise user engagement with the Library and meet expectations that users are forming from other services.

The Catalogue is Dead, Long Live the Catalogue, Part 3 (Visual Search)

Despite the advent of graphical user interfaces about thirty years ago at Xerox PARC, most catalogues are built on text. Libraries had their origins in text, books and other written documents and, in many cases, that is what our institutions are still known for (despite the fact that libraries do much more than that. The focus on books and text in our collections has also influenced the design of our catalogues. From my unscientific sample of major and minor library catalogues, I find that almost all catalogues are fundamentally drive by text: all the fields are in text, input is text and all the results are textual. Don’t get me wrong – I love text. As Thomas Jefferson remarked, “I cannot live without books.” Reading and writing is my preferred learning style (though I very much appreciate a well crafted lecture) but I recognize that other styles exist out there and it is important for me to learn about them even if they don’t feel natural.

In my understanding of the concept, visual search can mean at least two different results: searching for and/or displaying images or displaying search results using visuals that go beyond lines of text. Although some researchers are working on searching images directly, most systems I am familiar with (e.g. Google Image Search) use meta-data such as HTML tags or catalogue details to locate images. Such searching on Flickr can often produce interesting ideas and amusements though the results are uneven in quality. The other type of visual search is more about interface – showing results to the user such as tag clouds (e.g. tag cloud of the books at LibraryThing) or other methods. Of the two, I think that libraries are more likely to be interested in working on visual display of search results but the other type is certainly still of interest, particularly as large collections of photographs are digitized.

Based on experimentation with a few different Web search engines (are there library catalogues using it out there? If so, please let me know in the comments), my impression is this feature is not ready for prime time. Of all tools I tried, I found Spezify to be the most fun if quirky (it mashes together tweets, with images and webpages; doing a search on a city is fun). This kind of search is still only of interest to those who enjoy experimenting with such tools – I don’t know that it could be used to find something specific as yet. The experience of visual search could best be described as akin to browsing the book stacks of a library; accidental discovery is the order of the day but not much more.

Has anyone out there found a really good visual search tool? How does it work? I have a feeling I may have missed some good examples of visual search – would anyone care to correct me with a stellar example?

The Catalogue is Dead, Long Live the Catalogue, Part 2

Today’s post will investigate faceted search, an innovative that streamlines going through search results. I first discovered faceted search by using the catalogue at the University of Toronto where I studied for my Master of Information Studies degree. It was introduced as part of a major catalogue upgrade and it is the feature that I use most. As the Library has such a vast collection, I almost always use facets to limit by language (as I did in the example at the top of this post but I also often limit by library and publication date. Some of this could have been accomplished with the advanced search options but faceted search lets me eliminate results that I am not interested in. Based on some recent OCLC research, it looks like I am in the minority however; users they studied like the option but rarely used it.

Technologically, faceted search only became available this decade but the concept has a deeper history. Noted Indian library theorist S.R. Ranganathan is credited (who proposed a colon based scheme) with inspiring one company, Endeca, in the development of its faceted search tools. This is another example of the long and productive inspiration that library science has provided to IT development – I have also heard that citation analysis served as inspiration for the founders of Google. Some may think that the arts and sciences of librarians are under threat from computers and search engines, but this view could not be more mistaken. Collaboration has been the rule in the past and that looks set to continue.

Why is faceted search important for libraries? It matters because it encourages thinking about taxonomies and how information is organized. This is one of two major types of information retrieval according to the Special Interest Group on Information Retrieval of the Association for Computing Machinery which stated in 2006 (Thanks to Wikipedia for pointing this out to me):

* Navigational search uses a hierarchy structure (taxonomy) to enable users to browse the information space by iteratively narrowing the scope of their quest in a predetermined order, as exemplified by Yahoo! Directory, DMOZ, etc.
* Direct search allows users to simply write their queries as a bag of words in a text box. This approach has been made enormously popular by Web search engines, such as Google and Yahoo! Search.

I’m sure that most searching people do involves the use of direct search methods, so any switch to taxonomy based methods will be difficult. Facets can help organize information better, but people resist them as they are unfamiliar. The other reason that I think facets are worthwhile is that the better demonstrate the different criteria by which a given item is catalogued. When working with millions of books or other documents, this type of organization makes the task go by faster. It is especially needed in a large research institution where the very richness of the collection can defeat efforts to find something relevant. The example shown at the top of this example is organized as a series of text boxes, but that is not the only way to display it.

My question for readers today is whether you find faceted search to be an improvement over non-faceted systems? For librarians; does it make it easier to educate users about collections are organized?