Info & Interaction Design: Finding Information

Mick McQuaid



Finding Information

In the future, attention will be our most precious resource.

Search engines

  • Revelation of personal information when you search
  • What do you think? Should you be compensated?
  • Read Page et al. (1999) and Wikipedia on PageRank

Limits of search engines

  • Search by example
  • Search for things for which you have no name
  • Link rot

Conversational interfaces

  • Initial hype
  • The long game
  • First mover advantage vs market dominance
  • Corrosive influence of OpenAI on StackOverflow

Information credibility

Information credibility concepts

  1. Technical knowledge, skill or expertise
  2. Consistency of actions, values, meathods, measures, principles, expectations, and outcomes (definition of journalistic integrity from Wikipedia)
  3. Objectivity
  4. Pecuniary Interest
  5. Agreement with ideas and values held by the recipient
  6. Community membership
  7. Precision (variance)
  8. Accuracy (bias)
  9. Falsifiability (using scientific method)

Getting help

Exercise: comparing help for two browsers

Form an ad hoc group. Identify two browsers, such as Chrome, Firefox, Safari, or others. (Firefox and Chrome are easiest to study because they are heavily programmable and offer a lot of customization possibilities that may require help, such as skinning, global or domain-specific CSS add-ons, and other plugins.) Contrast the Youtube videos and user communities offering help for the two browsers.

Compare the health of the browsers in terms of instructional videos. Identify features of videos that alter your perception of the video. This could include things like the presence of ads before the videos (what does that tell you?), logos on videos, tenor of discussions, propensity of video maker to reply in discussions, number and range of videos by maker, presence of features like channels to organize videos, and more.

Compare the communities supporting the two browsers and identify differences in focus, emphasis, direction, and mission. Be specific about numbers of posts, recency of posts, topics of posts, and other salient features in community forums. What is the attitude of moderators? Do the moderators express an attitude? How transparent are moderation features?

A sub-sub-sub-sub-section


Pictures accompanying analytics articles always feature a magnifying glass

Google analytics

The logo for Google Analytics in focus

Gaming the system


data about data

Information Architecture

The Information Architecture Institute offers the following definition of information architecture in their pdf, referenced in the Wikipedia article on Information Architecture.

We define information architecture as

  • The structural design of shared information environments.
  • The art and science of organizing and labeling web sites, intranets, online communities, and software to support usability and findability.
  • An emerging community of practice focused on bringing principles of design and architecture to the digital landscape.

Information architecture tools

  • conceptual
  • commercial

baby busy box

Information hiding

Information comparison

Organizational information maturity

Da real woild jist ain’t like dat!

—Someone in an information-immature


Page, Lawrence, Sergey Brin, Rajeev Motwani, and Terry Winograd. 1999. “The PageRank Citation Ranking: Bringing Order to the Web.” 422. Stanford InfoLab.
Pirolli, Peter, and Stuart Card. 1999. “Information Foraging.” Psychological Review 106 (4): 643–75.
Proença, Diogo, and José Borbinha. 2016. “Maturity Models for Information Systems - a State of the Art.” Procedia Computer Science 100: 1042–49.
Rieh, Soo Young, and Brian Hilligoss. 2008. “College Students’ Credibility Judgments in the Information-Seeking Process.” In Digital Media, Youth, and Credibility, edited by Miriam J. Metzger and Andrew J. Flanagin, 49–72. Cambridge, MA: The MIT Press.
Spruit, Marco, and Katharina Pietzka. 2015. MD3M: The Master Data Management Maturity Model.” Computers in Human Behavior 51 (October): 1068–76.
Viviani, Marco, and Gabriella Pasi. 2017. “Credibility in Social Media: Opinions, News, and Health Information—a Survey.” WIREs Data Mining and Knowledge Discovery 7 (5): e1209.



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