Sweeny group think-ias2015

transcript

Hilltop Algorithm Quality of links more important than quantity of links

Segmentation of corpus into broad topics

Selection of authority sources within these topic areas

Hilltop was one of the first to introduce the concept of machine-mediated “authority” to combat the human

manipulation of results for commercial gain (using link blast services, viral distribution of misleading links. It is used

by all of the search engines in some way, shape or form.

Hilltop is:

Performed on a small subset of the corpus that best represents nature of the whole

Authorities: have lots of unaffiliated expert document on the same subject pointing to them

Pages are ranked according to the number of non-affiliated “experts” point to it – i.e. not in the same site or

directory

Affiliation is transitive [if A=B and B=C then A=C]

The beauty of Hilltop is that unlike PageRank, it is query-specific and reinforces the relationship between the

authority and the user’s query. You don’t have to be big or have a thousand links from auto parts sites to be an

“authority.” Google’s 2003 Florida update, rumored to contain Hilltop reasoning, resulted in a lot of sites with

extraneous links fall from their previously lofty placements as a result.

Photo: Hilltop Hohenzollern Castle in Stuttgart

Topic Sensitive Ranking (2004)

Consolidation of Hypertext Induced Topic Selection [HITS] and PageRank

Pre-query calculation of factors based on subset of corpus

Context of term use in document

Context of term use in history of queries

Context of term use by user submitting query

Computes PR based on a set of representational topics [augments PR with content analysis]

Topic derived from the Open Source directory

Uses a set of ranking vectors: Pre-query selection of topics + at-query comparison of the similarity of query to topics

Creator now a Senior Engineer at Google

Caffeine (2010) Indexing infrastructure

Made it easier for engineers to “add signals” that impact ranking

Pre announced and open to public testing

Panda (2012) Originally thought to be about content quality. Then expanded to machine mediated judgement of user experience. UX and IA are now the odd man out in designing experience for users. Google now determines quality of user experience and content with UX metrics? Clickthrough, Engagement, Satisfaction

Hummingbird (2014)

Comparison of search query to general population search behavior around query terms

Revises query and submits both to search index

Confidence score

Relationship threshold

Adjacent context

Floating context

Results a consolidation of both queries

Entity=anything that can be tagged as being associated with certain documents, e.g. Store, news source, product

models, authors, artists, people, places thing.

Query logs (this is why they took away KW data – do not want us to reverse engineer as we have in past)

User Behavior information: user profile, access to documents seen as related to original document, amount of time

on domain associated with one or more entities, whole or partial conversions that took place

Alternative to figuring out something that really works, to working with UX, to find an alternative to the SEO guns

and religion of keywords and links

UX, Content Strategy, IA

Users strive to make sense of reality as they move through situations, time, and space

Users encounter gaps in their knowledge and see these as barriers

Users seek to “bridge” the gap and reach their goal (a reality that again makes sense)

Users don’t know what they don’t know. So, they start looking from a point of ignorance. IR systems have a hard

time grasping this.

Searchers use a variety of techniques and resources Safe to say, not many of our users “surf over” to the product sites to “check out the action”. Our users are more about “directed browsing” an unstructured and opportunistic search, stopping along the way to get berries, with a specific objective in mind. When our users come to our sites each click is a question regarding what they think they need to know. Either we answer the question, provide them with enough information to refine their search and continue on, or fail them completely where, in frustration at being confronted with yet another information problem, they resort to the search box in the upper right corner.

(What is Browsing Really: Bates 2007) 4 elements to browsing behavior: glimpsing, selecting/sampling, examining,

acquiring/discarding. Browsing does not equal scanning (differentiated behavior)

“We define browsing as movement in a connected space. In order to achieve this movement, people undertake

certain actions: they shift their gaze, they alter their position, they skip over things, they glance at things briefly, from

afar, or close up, they back up, they pause or stop and they respond to interesting phenomena (Kwasnik 1992)”

Web search engines have not been good for browsing, recent attempts of support with facets, filters (spatial,

temporal)

Whenever possible, we should empower our users with fine-tuned navigational aids so that they can find what they

are looking for themselves.

Dynamic Semantic Clusters: Where User Experience Begins Mark Baker: Content Strategy Forums: July 25, 2014 http://csforum.eu/articles/dynamic-semantic-clusters-where-user-experience-begins

Resource: Pew Internet Trust Study of Search engine behavior

http://www.pewinternet.org/Reports/2012/Search-Engine-Use-2012/Summary-of-findings.aspx

How to search:

56% constructed poor queries

55% selected irrelevant results 1 or more times

Get Lost in data:

33% had difficulty navigating/orienting search results

28% had difficulty maintaining orientation on a website

Discernment

36% did not go beyond the first 3 search results

91% did not go beyond the first page of search results

Resource: Using the Internet: Skill Related Problems in User Online Behavior; van Deursen & van Dijk; 2009

VISUAL COMPLEXITY & PROTOTYPICALITY

The results show that both visual complexity and proto-typicality play crucial roles in the process of forming an

aesthetic judgment. It happens within incredibly short timeframes between 17 and 50 milliseconds. By Comparison,

the average blink of an eye takes 100 to 400 milliseconds.

In other words, users strongly prefer website designs that look both simple (low complexity)

and familiar (high prototypicality). That means if you’re designing a website, you’ll want to consider both factors.

Designs that contradict what users typically expect of a website may hurt users’ first impression and damage

their expectations.

August 2012

Resource: http://googleresearch.blogspot.com/2012/08/users-love-simple-and-familiar-designs.html

Put the sidewalks where the footprints are

Resource: Stuart Brand: How Buildings Learn

Fell into designing for the technology

I made it look pretty

Wordpress sites: Spot them from afar…HUGE spanning hero and infinite scroll neither of which users like much

IR systems have built in functional complexity to accommodate multiple aggregators and actors that are opaque to

users (black box)

The information system has the role of supplying knowledge and is not always the sole supplier of output

Role of knowledge support of specific action

Information System/Soft System: information as socially constructed

Information Engineering: information as a concrete phenomena

Problem solving encompasses system, cultural and strategic concerns

SSM incorporates system learning and experiential learning and applies to problem-solving

IR systems have built in functional complexity to accommodate multiple aggregators and actors that are opaque to

users (black box)

The information system has the role of supplying knowledge and is not always the sole supplier of output

Role of knowledge support of specific action

Information System/Soft System: information as socially constructed

Information Engineering: information as a concrete phenomena

Problem solving encompasses system, cultural and strategic concerns

SSM incorporates system learning and experiential learning and applies to problem-solving

Soft system Methodology (SSM)

SSM grew out of the failure of systems engineering-excellent in technically defined problem situations-to cope with

the complexities of human affairs, including management situations. As system engineering failed we were naturally

interesting in discovering what kind of approach could with problems of managing.

SSM is the logic-based stream (engineering) incorporating cultural and political streams to make judgments

between conflicting interests by setting up criteria on what is significant and how to judge?

Model the purposeful activity of the users to define the transformations to take place

SSM: A Thirty Year Perspective: Peter Checkland (2000)

We already do this in a manner of speaking except without the underlying systems part, hence the current unicorn

hunt for UX professionals

Assumptions:

• The adaptive whole includes contradictory systems

• The system will go through one or more transformation

Intersection and Transformation of SSM: Mathiassen, Lars, Neilsen, Asid (2000)

Idea is that there would be better systems of IT professionals had better understanding of the scope, nature, impact

of the system

User experience will be better if UX professionals have a better understanding of scope, nature and impact of

designs on IT (there are always trade offs)

SSM is about cycles of discussion, learning and debate – unlike IT system thinking that looks for absolute complete

solution every time

SSM uses system and psychological foundations to develop models of human behavior – measurement of these

models is problematic because not always quantitative

Answered for us and the client

Would this become the first deliverable after signing?

Precipitate the client questionnaire?

Stage 1: Express the current situation and surface the plurality of project team world views

Examine the background of the problem to expose issues, problems in structure, develop representation of relevant

domains. Used for identification of knowledge gaps, elicit discussion with all of the stakeholder groups

Stage 2: Uncover the Root definition = relevant systems that will provide insight into the problem. Used to ensure all

points of view and intersect considered

Select issues that warrant a closer look by project team

Develop alternative views

Explore creative scenarios

Drill down into specific organization processes

Stage 3: Conceptual Model: expressed by verbs, usually focused on 3 sub systems (knowledge, criteria,

application. Verbs are the first level of resolution, e.g. monitor and control.

Develop agreement and action plans through process of accommodation

Output = human activity system to create evaluation of the real world

Stage 4: Execute on action plans for purposeful activity

This is what I see when I read/hear about Agile UX

It is a virtuous cycle

The new-new thing

Multipolar experience where everyone has an opportunity to participate in delivering a satisfying experience

Serious play >> magical thinking

There’s lot of interest in design thinking these days – don’t care about that, care about what it means to us as

information professionals

Most of the work here has been done by agencies that are VERY successful (IDEO, frog). Mention that next time

your boss says they: can’t afford it, can’t sell it, can’t use it.

… A methodology that imbues the full spectrum of innovation activities with human center design ethos.

We thought that we were doing this…Wrong

It should be doable without custom dev

It has to make money or facilitate making money (that’s how they pay us)

Top down logic

Logically certain and verifiable conclusion

What does the data say

Validate thinking with metrics

Google would not be around today if it practiced deductive reasoning

Possibility over validity

I wonder over I know

1st step of reasoning is wonder, not observation

Logical leaps of the mind from data that does not fit the models

Actively look for new data points

Challenge accepted explanation

Infer possible new worlds

Experimental: nothing wrong with failure as long as it comes early

Flexible: accept that milestones cannot be predicted with certainty and projects take on a life of their own

Collaborative : silver buckshot instead of silver bullets

Inspiration: insights gathered from across resources

Ideation: ideas that become insights

Implementation: base ideas developed into concrete plan of action

prototypes

good not working model that inspires conversations

shared vision realized

nothing codified – spring board to meaningful changes (this avoids codified mistakes)

Design thinking does not occur in linear steps

Spaces demark different and related activities

Can loop back and forth between spaces

(NOT THE RFP)

(may have to think outside the problem space, e.g. Bill Gates wanting to bring internet access to sub-Saharan

Africa only to find out that they need clean water and electricity first)

Well constructed brief provides for serendipity, unpredictability and the capricious whims of fate

Prepares the soil for ideation

Need T-shaped folks here

Tools: brainstorming with cross discipline, diversity of participants, visualization and conceptualization

Group sort ideas

Discover client world views, environment, cultural and political influences

Surface interacting systems within organizations (client and ours)

Define user purposeful activities (what problems are we trying to solve)

Iterate the engagement

Shift thinking from optimizing for the technology to optimizing for the users

Navigation dominance

A true “home” page, start here and navigate to where you want to be

Broad band comes into its own and BIG pictures make a splash

Why Google started moving away from link-based relevance

Remember the unstructured problems? Intangibles?

They will attempt to derail the best laid plans.

Deliverables/Outcomes: Persona, Competitive Landscape review, Lifetime Customer Value, SWOT Analysis, KPIs

and Goals

Branding & messaging framework review

Client customer data

Demographic and Psychographic data (FB, Google affinities, social media channels (twitter, LI, etc)

Analytics: To see what we’ll be able to track.

Competitive Landscape Review

Client competitive data

Existing and emerging competitors

Industry news/trends

SWOT Review

Answered for us and the client

Would this become the first deliverable after signing?

Precipitate the client questionnaire?

Deliverables:

Content audit for gaps (keep, kill, demote)

Content strategy for opportunities

http://www.wsj.com/articles/SB106134872871015900

Because great architecture is not enough. This is Falling Water by Frank Lloyd Wright. The joke is that it lives up to

its name with

Cantilevered terraces (projections that extend well beyond their vertical support)

Structural engineer found that "after more than 60 years, Fallingwater was still moving." One side of the living room

terrace, he reported, had sagged almost seven inches.

Sounds like it worked for Wright more than for the client.

While we discuss whether there can be such a thing as a UX designer,