Conveying emotion in the digital space shouldn’t be so hard
Though the digital world increasingly allows us to communicate and share our experiences, we all still struggle to express ourselves and understand one another effectively in the most basic of human languages — emotions.
Our feelings truly matter. They are the cornerstone of our experiences and of consciousness itself. They are the foundation of our motivations, and contribute more to our behavior than we sometimes care to admit. It’s now increasingly understood that we don’t make any decisions without them. But there is a deepening tension between the extraordinary pace of evolution in software-based communications and the age-old need for emotional connection.
At the end of the day, what often matters more than anything else, is how we feel. And some of the most powerful feelings occur in understanding, and in being understood by, someone else.
In popular usage contexts such as texting and social media, currently available methods for communicating and understanding feelings are inadequate, frustrating, and potentially misleading. They hinder the work of researchers, brand managers, health care professionals, and others who are interested in utilizing emotion-related data, particularly regarding specific types and intensities of feelings. Software developers who would like to build or evolve websites, platforms and applications that provide for and leverage emotional expressions face serious challenges posed by the currently-available methods.
In this five-part series, we will outline these difficulties, summarize a set of criteria for more optimal solutions, and present a new platform designed to meet those criteria and humanize digital communications more fully.
Digital emotion isn’t easy
Why is it still so difficult for us to express and understand one another effectively, accurately, and efficiently? We share spontaneously and organically in social media, texting and email. We annotate and leave comments in response to journalism. We seize the opportunities offered in websites to tell businesses how we feel about our experiences with their products and services. And we respond to surveys about politics, the economy, our jobs, our preferences, and our perspectives. In our efforts to communicate our feelings, we write, select emoji and stickers, use 5-star ratings, complete Likert scales, and even send one another GIF’s portraying video snippets. But still, we struggle, because most available methods for expressing emotion are limited, imprecise, and potentially misleading.
Written words can allow for rich expressiveness but can all too easily be misinterpreted. A given word can mean more than one thing, and its meaning is often heavily dependent upon context, particularly when emotional context is important. Additionally, some people are extraordinarily wordy, while others are so sparse in their communications as to leave far too much to the imagination. Occasionally, the meaning of a word or phrase seems abundantly clear to most readers, but rarely to all. Too often, the meaning is not so clear at all.
The two messages below illustrate how ambiguous emotions and intentions can be when communication is attempted by written words only, particularly in the instances of brief online exchanges. There are simply so much risk for can misunderstandings, misattributions, and nights spent sleeping on the couch.
Likes & Thumbs
The ubiquitous but much-maligned “Like” button and the popular“thumbs-up/thumbs-down” system can allow us to rapidly and easily express some of our feelings. But these expressions usually represent only summary impressions, expressions of simple agreement or disagreement, statements of preference or opinion, at best. Mainly, these methods express what is referred to as sentiment. They rarely are useful for representing any sort of specific feeling, and offer no clear indications of feeling intensity. Unfortunately, they can also be used as an expression of simple acknowledgement or particularly with Like buttons, as a means of signing up for a raffle.
Certainly, it is easy for two people to render a “like” or a thumbs-up impression, while having very different feelings and reasons for doing so.
Emoticons, Emojis & Stickers (oh, my!)
Emoji (and their bigger kin, stickers) have been with us for awhile now, arguably representing some progression over old-school emoticons, which date back to 1982. But emoji are an ever-growing hodgepodge of kitschy drawings that lack any coherent basis for emotional representation, much less any meaningful method for accurately conveying any variations of intensity of feelings. And depending upon where they’re found, they may or may not have any labels to help us to select they according to the feeling we mean to convey. Their appearances do not necessarily convey any one feeling faithfully, and to make matters worse, their appearance is often not consistent across operating systems or platforms, if appearing on more than one platform is even possible (most stickers are not).
And, just what feeling DOES the smiling poop emoji convey?
Moving Picture Shows
GIFs (graphics interchange format) can do a good job of conveying feelings and emotions, though they don’t ensure that the feeling one means to convey is the one a recipient will infer.
Unlike emoji, they’re often listed with labels that can include emotions. However, the GIF content and the label sometimes seem at odds with one another. And, they do not necessarily clearly or consistently convey the intensity of the feeling a sender means to convey, even if the intensity of a given emotion IN THE GIF is fairly clear.
Likert responses can allow us to express degrees of agreement and disagreement or identification with concepts such as feelings. Similarly, various other forms of visual analogue scales can allow us express some degree of agreement and/or intensity of feeling. But these are usually seen as response formats to survey items, not as spontaneous methods for communicating feelings. One key reason is this: no one actually feels in five-point gradations. We don’t feel in 3, 4, 7, 9, or 10-point gradations, either.
Another reason these are less than optimal for expressing and understanding emotions is that they require people to estimate their feelings by comparing them to phenomena that bear precious little resemblance to the way we actually experience our emotions. They require us to imagine we’re comparing our feeling intensity to non-universal yardsticks, as in “how many inches along this stick I found in my yard, do I feel?”
The same is true for five-star rating systems, except that instead of asking us to liken our emotions to a two-dimensional line, the sort of require us to consider how “heavy” our feelings might be. This is akin to asking us to compare our feelings to the number of rocks in a bag, that bag being capable of holding a finite number of rocks. Sometimes, the maximum prescribed number of rocks is insufficient.
These formats suffer one truly fatal flaw: they require us to quantify our feelings, and to provide our own “measurement” for them in ways that are neither intuitive nor necessarily accurate.
The Bottom Line
The situation is frustrating for digital media users who simply want to share their emotions and experiences and understand those of others with a minimum of confusion and frustration. This is because most of the common and traditional means for doing so are limited, inconsistent, and potentially confusing.
Our feelings tell us what matters, how much, in what ways, and help us to decide what to do. That is to say, they provide useful information. That information can be useful to others who care how we feel as well, including scientists, actuaries, and brand development officers. Increasingly, they seek to accurately measure the frequency, types, and intensities of emotions people experience, and to derive insights about human behavior.
However, to the degree that emotion measurement is imprecise or misleading, the quality of those insights are compromised. In Part 2 of the series, we’ll look at those difficulties more closely and move toward an expanded view of potential solutions.