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Search & the Emotional Response to Information Seeking

Discover how developments in neuro-information science and biometrics are shaping the future of information seeking and personalizing the search experience.

Search & the Emotional Response to Information Seeking

What if search engines delivered information for you sorted by your emotional state?

Can a search result be influenced by situational awareness?

If we create personalized search results and promote purposeful, targeted information in social media outlets, how do digital marketers adapt to emotional responses from people as they browse and choose?

The future for information seeking is already being explored in the fields of neuro-information science and biometrics.

The Searcher Journey

If you were to watch search engine keywords and phrases entered from around the world all day long, you would not only go crazy from boredom, but you also would not get a clear insight into the people searching for answers.

You would not have the slightest clue about why they asked their question or chose their words, but perhaps you have access to data about where they are, the computer device and browser they used, and their operating system.

What additional types of information are helpful to know for your webpage design? Are there additional metrics useful for marketing and writing content?

Where are your user personas in their search journey?

Back in March, Jason Hennessey wrote about search journeys in “Google’s Shift from Answers to Journeys: What Does It Mean for SEO?”

“Search Journeys looks at context – and uses that knowledge to show users content that is most relevant to where they are at in their journey rather than simply giving them an answer to a question.”

This “where they are in their journey” will help with understanding the future of search.

To improve wayfinding, we can deep dive into human behavior and consider emotions, environment, and state of mind as natural connections to user interface design and information architecture design.

The layer of searcher behavior we are more familiar with is measured in tasks, actions, and physical data.

Google, for example, delivers answers based on where we have been and our previous search history and presents what it concludes we will look for next. This may work for people who are the sole user of their computer devices.

What about families that share one computer? If you work from home, your search history may be a combination of work and home life. There are many reasons search habits may change.

The first thing people do when they are in an emergency situation or have received bad news about a health diagnosis is to get help.

Our expectation when we are upset or frightened is to quickly find accurate information when we turn to the web.

Researchers are looking at how our moods and emotional responses to information we see online is used to write content intended to assist us and manipulate opinion.

Trust, Facts & Information Mining

My grandfather had a favorite drawing he taught me when I was a teenager.

It was of a wooden post and rail fence in the country with this little guy reaching up and trying to see over it.

All we drew was his curled fingers over the top rail, an oversized nose and large eyes resting on the rail gazing out at the world. I doodled it for hours in class and after class in school.

We don’t talk with our neighbors over fences anymore.

People seek information by reading books, going to the library, reading print newspapers, going to church gatherings, attending parties and talking to friends, listening to the radio, and watching TV.

Choices vary by age, country, culture, disability, personal preference, and habit.

The least factual deliverer of information is the web, especially social media, but nevertheless, it is the first place to know what’s happening in the world.

Facebook trust took a major hit when it was discovered it allowed Cambridge Analytica to harvest personal data of millions of Facebook profiles without their consent for political advertising purposes.

Twitter is used by government leaders, thought leaders, celebrities and businesses for commentary, opinion, and announcements.

Advertisers and affiliate marketers learned to use social outlets to spread misinformation to sell products.

With time, more people using the internet are doubting the accuracy of the information they see, and turning to fact-checking websites, but even those types of websites are not always accurate.

Where do people go to get information they trust?

The source for answers is a wide-open variable. And, thanks to machine learning and AI technology, our human responses to information are the new play toy for research.

What happens when information search results are influenced by human behavior?

Human Behavior on the Go

What emotions are we feeling when we search for information?

What are we losing when we allow access into our personal lives so that we might receive personalized website engagement and information seeking?

A recent SEJ article, “Google to Capture & Learn Our Emotions on a Smartphone Camera?” by Bill Slawski, introduces a Google patent called Graphical Image Retrieval Based On Emotional State of a User of a Computing Device.

In this patent, a searcher’s reaction to search results might be used to rank those results. It is related to another patent from three years ago on biometrics.

“The Biometric patent told us that it would potentially change the rankings of results based upon searchers’ reactions to the search results they were seeing.”

A new Pew Research Center study on facial recognition found that the public trusted technology companies (36%) or advertisers (18%) to use facial recognition responsibly.

Would seeing facial expressions help deliver an appropriate response in emergency situations?

I refer to neuro-information as “human behavior on the go” because of the enormous exposure to unfiltered content produced by people in various physical, mental and emotional states to people with various physical, mental and emotional states.

When you add in an agenda, the integrity of the information is fractured.

Microblogging formats, such as in Twitter with its limited character count, and Facebook and Instagram comments, allow users the spontaneous ability to forward, mention, and rapidly respond to topics.

Twitter shapes opinions and creates actual trending topics based on our reactions and responses.

Emoticons and images add visual emphasis to words to increase views. For example, we respond to heart icons and images of people making facial expressions of disbelief and shock.

Medium added hands clapping to mimic applause for articles from readers.

From politics to entertainment, culture and the stock market, microblogging is a fast way to reach the masses in a hurry and convince them into making choices they may not have considered.

Influencing Search Results

Behavioral financial theory, based on human financial psychology or behavioral economics, was part of a research paper about the stock market and social media influence.

Researchers studied sentiment analysis and high-speed trading. They found investors’ moods are influenced by opinions, resulting in a “herd” effect, and referred to as “contagion” in behavioral financial theory.

In other words, if someone on Twitter claims the sky is falling, behavioral finance theory economics points to the fear of losing money, an investor’s worst fear. Investment decisions are based on moods, opinions and public sentiment rather than statistics and rational research, the more traditional practice for investors.

Can we help a search engine understand not only the semantics of a search query but the context from where the search is made?

Certain types of searches are common, such as by location (“landscapers near me”) and reputation (“top 5 dentists near me”). How we perform local searches is worth inspection if you are designing web sites for a local area and hoping to appear in search engines.

Ask your friends how they search for local shops, real estate, auto dealers, medical offices or movie theaters, and you will quickly realize that everyone has their favorite habits.

Some speak into their cell phone.

Some type keywords.

Some people choose to avoid search engines and go directly to online maps, or a mobile app like Waze or a travel app.

We also use the web to search for flights, food, and products to purchase. Many people use assistive devices to access the web.

Would you know when a blind person using a screen reader is looking for a gift for a friend or wants to order pizza delivery?

Probably not.

But imagine if you targeted them specifically in your marketing strategies and brought them to a website that is accessible?

In the future, ranked webpages may be directly related to you, personally, in the moment.

Knowledge Graph

Companies gathering data about us hope to use the information to make money.

When we are upset or in a hurry, we scan quickly. We retain large amounts of information to go back and forth, in and out of websites.

To sneak past our imagined security (there is none) and perceived privacy (there is none), we are subjected to:

  • Facial recognition apps.
  • Quizzes and games on Facebook.
  • Surveys.
  • Those pesky free downloads for ebooks that require your phone number and firstborn puppy to gain access to it.

Back in 2001, I was hired to test the user interface and functionality of a software application designed to store information from customer service call centers for a major corporation.

The data was used by various departments, including marketing, to better understand customer complaints, feedback, and the types of support they needed.

The most frequently entered complaint from customers was their desire to speak to a human by phone.

Eventually, a system was built for an online version to collect customer service data consisting of three survey questions that were rotated to customers who visited the main website. This method was later abandoned because it was impersonal and invasive.

The biggest complaint was that customers wanted to speak with a “real person” by phone. They did not trust information from the internet.

In 2012, Google introduced Knowledge Graph to deliver a more robust response to search queries that went beyond keywords and rank.

By compiling data from various sources, a knowledge panel could be erected in a sidebar showing images, links and text used to answer a question with greater detail.

Google crawls the web, adding people, places, and things to the knowledge panel that it decides to put there.

To SEOs, helping Google “decide” is a bullseye too good to ignore. The challenge is exciting, like two knights in a sword fight hoping to impress the King and Queen.

For everyone else, they have little say in what they read in a knowledge panel and are asked to trust the accuracy of that information or keep searching.

In 1993, Carol Kuhithau developed the Kuhithau Information Search Process model, which is still widely used for testing.

The ISP model incorporates feelings, thoughts, and actions in six research stages that a user conducts. These stages are:

  • Initiation
  • Selection
  • Exploration
  • Formulation
  • Collection
  • Presentation

Research studies found that searchers go through a variety of different feelings as they proceed through the six stages such as:

  • Uncertainty
  • Optimism
  • Confusion
  • Frustration
  • Doubt
  • Clarity
  • Sense of direction
  • Confidence
  • Relief
  • Satisfaction
  • Dissatisfaction

Their actions move from seeking relevant information to seeking pertinent information.

The searcher journey is anything but a smooth ride.

The Future of Information Seeking Is Personal

I watched someone reach for his phone to research workman’s compensation after a discussion with friends about the problems he was having with his employer.

We all laughed when the first result was from FindLaw.com. It was exactly what he needed and matched the advice his friends were giving him.

The Netflix series, “Better Than Us”, is a sci-fi look at the future where humans and robots co-exist and access to information of all kinds is obtained by a flick of the wrist.

Arisa, the main character, is a uniquely different experimental robot able to detect emotions by studying the physical state of humans and learn empathy.

Arisa is stolen by George Safronov and this begins the winding story of a futuristic Moscow packed with technology such as calling someone and viewing content on the skin of a wrist.

One scene made me think of how personalized search might be someday.

Safronov is in heaps of trouble and in the middle of doing bad guy things, slumps to the floor, raises his wrist, and verbally begins a search that produces a large, transparent screen directly in front of where he is sitting.

He asks to see a warm, tropical island. The screen floating in the air takes him to a series of islands that he is familiar with already.

He defines his criteria one or two more times until he finds the tropical island that he can escape to with the least amount of hassle.

It took about four screens, with a computer voice answering his questions and the last action to give a voice command to book the flight, which the computer took care of immediately for him.

Since he was in an agitated state, in a hurry, sweating and exhausted, he was not in the mood for browsing. He required pertinent information as fast as possible.

Neuro-information science opens the door to new ways of thinking about how we seek information, deliver and apply that information.

There is a study on the role of eye movements and physiological signals in search satisfaction prediction for example.

Rather than studying click-throughs, mouse movements, and query reformulation, neurophysiological signals capture evidence that is not directly expressed or expressible.

Another study, Neuropsychological Model of the Realization of Information Need, examines information retrieval and information need (IN). The introduction is fascinating.

“IN refers to the complex concept: at the very initial state of the phenomenon (that is, at a visceral level), even the searcher may not be aware of its existence.”

When we need help, we can find an app. For example, ThinkDirty is an app that will evaluate if a product’s ingredients are safe to use.

If personalization of information seeking on the web is truly customized in the future, we may not learn different perspectives, opinions, or debate ideas.

However, we might control the stores we buy from based on our political or religious beliefs.

What if we could control what we see?

Is the future of the search journey going to isolate us or divide people even more?

While some SEO professionals haggle over what tactics contribute the most toward ranking higher in search results, the missing link is responding to humans.

We do not have the ability to determine the truth factor in the information we find and search engines are not the holy grail for conversions.

Web conversions depend on websites and software with universal user interfaces that work for everyone. Will the future allow information seeking without bias?

In the future, we may get machine learning systems to have empathy and search engines will know how to provide personalized searcher experiences.

Or, we may go outside and chat with our neighbors next door.

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VIP CONTRIBUTOR Kim Krause Berg Owner at Creative Vision Web Consulting, LLC

Kim Krause Berg, CPACC Accessibility and QA Analyst, Accessibility, BM Technologies, Inc. (BMTX) f/k/a BankMobile, owns Creative Vision Web Consulting, ...

Search & the Emotional Response to Information Seeking

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