Is deception detection easier when we have verbal cues? Could it even be harder?

A lot of sensory input goes into our ability to detect deception, but it is hard to tease out the role of verbal and nonverbal cues. We train you to look for both, but a new study seeks to break down the question and look at exactly what helps us determine whether somebody is lying.

This research combines expertise in communications and criminology by creating an experiment where participants are exposed to an interrogation record and tasked with evaluating whether the interviewee is lying. This is varied between multiple cases where participants get a full videotape, an audio clip, or just a transcript.

This builds on research finding that we rely on mental shortcuts in order to more effectively detect deception. The study authors broke down biases into truth, visual, demeanor, and expectancy violation biases.

Each of these is relevant. For instance, truth bias leads us to assume truthfulness in others, while expectancy violation bias general sees unusual behavior as constituting a lie. Perhaps more relevant to the question at hand, visual bias emphasizes visual stimuli in detecting deception, while demeanor bias sees certain communication styles as credible ones, regardless of the truth.

Unfortunately, none of these biases are necessarily accurate measures of deception detection. In fact, one of our past blogs has pointed out that the common belief that people fail to make eye contact when lying is a myth, showing how our expectancy violation biases create problems.

By exposing participants to different levels of verbal and visual cues, the study authors sought to explore each of these biases. While past research has explored similar topics, it tends to have focused on short, less than one minute clips. This prevents an understanding as to whether interviewers can use a longer exposure to better understand deceptive behavior.

Essentially, this experiment hypothesized that the more nonverbal cues available, the more likely the participants would assess the interviewer as truthful, with the full videotape exemplifying this tendency.

Interestingly, deceivers were generally believed the most when participants had access to the audio and visual components of the interview, but this was not the case for those telling the truth. Instead, perceptions of truthfulness peaked with access to audio but began to decline when visual components were involved.

The researchers saw this as broadly confirming the important role of cognitive bias. For instance, deceivers likely paid closer attention to their demeanor (in order to hide their lie), resulting in truth-tellers being likely to showcase more unusual behavior and thus introducing the demeanor bias.

The real lesson here is that our cognitive biases may mislead us, but that doesn’t mean that heuristics are all bad news. Instead, empirical science has developed a more valid framework to rely on.

And it is that sort of framework that Humintell regularly trains people in. One great way to learn empirically-validated lie detection is to get trained in our expert techniques.

Humintell is proud to announce that we have launched a new version of our reading people training package, with some exciting offers exclusively for you until the end of the month!

While this new program will build off of the same people reading themes that Humintell has always specialized in, the new course, with three modules, will help integrate various aspects of nonverbal behavior analysis in a more comprehensive way than previous packages. These modules are an ideal tool for helping you learn how to apply people reading skills to the real world.

The first module focuses on some of the bigger conceptual issues that followers of this blog may have some familiarity with. What does it mean to read people? This will be broken down into some of the important differences between verbal and non-verbal cues, for instance.

While this blog has worked to give you some familiarity with these techniques, this first module is a great way to show you how all of the pieces fit together into a helpful strategy.

With a better integrated understanding of people reading, trainees can proceed to the second module which helps more specifically connect ideas to actual practice. Sure, you have read about a lot of expressions and nonverbal behavior, but can you actually detect them? This module can help show you how to apply these ideas, as well as show how they vary on a case by case basis.

Finally, dedicated trainees will situate this people reading strategy into an emotionally-specific context with the third module. The connections between people reading and emotions will be explored, with an eye to applying the aforementioned skills to an emotional context.

This is of course the crux of the matter, where we not only learn what goes into reading a person but how we can detect their actual emotions or affective states.

While many concepts like microexpressions are familiar to loyal readers, the application process is always more complicated than one would think. By letting trainees learn about these concepts in an interrelated way, you can see the practical side of people reading in ways that following this blog will never match up to.

That said, the core training of this module can always be expanded! After completing your training, each new piece of information presented on this blog can better be situated. We never stop learning, after all.

Of course, this is not the final word on any of these topics. As you know, Humintell offers a host of people reading programs, and this month they will all be much cheaper! A lot of our programs are being slashed by hundreds of dollars!

If you have enjoyed this blog, then this is the logical next step. Hope to see you there!

 

Emoticons are becoming increasingly prevalent in our internet and social media strewn social landscape, but how effective are they at conveying emotion?

This point is often made by those who find these somewhat silly symbols pretty ludicrous, but their flaws may run a little deeper. While prolific in our culture, representing a smile with J may not effectively translate across cultures. This may seem odd given that an expression of happiness is universal across cultures, but new research seeks to balance the role of universal emotions amongst subtle cultural differences.

A group of researchers led by Dr. Kohske Takahashi conducted a series of experiments where they asked participants from Cameroon, Tanzania, and Japan to identify whether various emoticons were Happy or Sad. This included smiling and frowning faces but also more neutral visages. What is most interesting is that these experiments were conducted among a wide swath of people, including hunter-gatherers, farmers, and city dwellers, in an effort to see how the emotional recognition would vary by more than just country.

While the researchers did not test it, presumably the vast majority of American respondents would identify as representing happiness. This is likely due to our culture’s incredible saturation with emoticons, and they sought to test something similar by contrasting Japan, where emoticons are prolific, with Cameroon and Tanzania, where they are rare.

Perhaps unsurprisingly, Japanese respondents were much more likely to identify emoticons than their African counterparts. What is a bit more surprising is that, among participants from Cameroon and Tanzania, city dwellers were no more likely to identify them than rural farmers, despite the frequent use of social media in those countries’ cities.

The researchers declined to make strong conclusions about that, as they did not control for prior familiarity with emoticons. While this may have helped resolve the question, they found similar results across variants of emoticons which included Western versions, such as :-), Japanese versions, such as (^_^), and more overt representations like . If the problem were simply a lack of familiarity, it is pretty safe to contend that the generic representation would still be more recognizable.

Instead, Dr. Takashi’s team concluded with deeper considerations. They argued that, despite the universality of emotional expressions, methods by which to convey those emotions are what vary. A depicted smiling face may not represent the sender’s emotion but instead could simply represent the idea of emotion. The distinction would stem from one’s familiarity with using emoticons to convey expression online, rather than a familiarity with just seeing them.

Alternatively, there are a host of other cultural barriers in online communication. Many keyboards have different signs of punctuation, and many languages are formatted on the page quite differently (such as with text moving right to left or up and down). Finally, because many cultures focus on different parts of the phase, the expression portrayed in simplistic emoticons loses a lot in translation.

But this study also conveys even deeper notions. Despite the promise of universal basic emotions, there remain huge cultural differences. While I could detect emotional expressions among American and Japanese counterparts, this may get much harder with those from Tanzania, as I am not familiar with the nation’s culture or its people.

Still, we want to be able to read people from all sorts of countries! This is why, in addition to a people reading workshop, Humintell prioritizes our efforts to train you in cross cultural communication by focusing on actual universal behaviors, not those conveyed by a keyboard.