What does honesty look like (statistically)?

Certain linguistic features (e.g  reference, modality) facilitate deception because they are malleable to context and flexible to interpretation. My first blog post showed that deceptive communication contains ‘outliars’, portions of texts with an unusually high concentration of these linguistic features; in the second post we saw that the linguistic hotspots where these features cluster can be taken as ‘points of interest’ worthy of further investigation. Of course, liars do not have a monopoly on the use of modals! Furthermore, truth-tellers can sometimes be mistaken for liars due to nervousness, fear of disbelief, or perceptions of powerlessness (known as the ‘Othello error’). So what does honesty (non-deceptive) communication look like?

sharapova mistake

In my Standford Decepticon 2017 conference paper I tested the ‘Outliar’ investigative linguistic methodology on honest admissions of doping – true confessions – by the following five sports persons and professionals:

true doping confessions.png

The Maria Sharapova case took the tennis world by surprise (she was the first high-profile female tennis player to fail a drug test). In 2016, Sharapova was banned from competition after testing positive for meldonium during the Australian Open in January of that year. Meldonium is a heart medication that was found by the World Anti-Doping organisation (WADA) to be particularly popular amongst sports persons from Russia and Eastern Europe, perhaps due to its ability to block the body’s conversion of testosterone to oestrogen. Having placed meldonium on a watch list in 2015, WADA had fully prohibited the substance from January 1 2016, two weeks before the Australian Open. Following the failed drug test, Sharapova admitted she had been taking meldonium as medication since 2006 and stated that she had negligently and inexcusably missed the communications from WADA prohibiting its use.

Linguistic analysis of the explanation Sharapova gave to fans via her Facebook page shows two ‘outliars’ at the beginning and end of the post (see Figure 4 below).

Sharapova outliar graph

[1] I want to reach out to you to share some information, discuss the latest news, and let you know that there have been things that have been reported wrong in the media, and I am determined to fight back. You have shown me a tremendous outpouring of support, and I’m so grateful for it.

[13] I have been honest and upfront. I won’t pretend to be injured so I can hide the truth about my testing. I look forward to the ITF hearing at which time they will receive my detailed medical records. I hope I will be allowed to play again. But no matter what, I want you, my fans, to know the truth and have the facts.

Figure 3: Outliar analysis of Maria Sharapova’s 2016 Facebook post and outlier extracts.

Sharapova begins her post by suggesting she has been a victim of unjust media coverage. It had been widely reported that she had received five ‘warnings’ about the upcoming change to the WADA regulations. Sharapova agreed that she had received newsletters with links to the WADA rule changes but argued that these were ‘communications’ rather than warnings through which one had to “hunt, click, hunt, click, hunt, click, scroll and read” in order to find information about the prohibition. Sharapova ends her post by strongly maintaining that she is being honest about her genuine mistake (of using Meldonium as medication after the ban).

These anomalous extracts are particularly emotional when compared to the main body of this post, in which Sharapova gives specific details about all the communications she did receive (see yellow highlighted text in Figure 4 below). There is a lot of literature that suggests specific details are a strong indicator of veracity in legal genres such as witness statements. (Professor Aldert Vrij’s research on Criteria Based Content Analysis is a good place to start.) These anomalous extracts could just be ‘Othello errors’ that are confusing emotional intensity for deception.

Sharapova FB 1cSharapova FB 2c

Figure 4: Maria Sharapova Facebook post, March 2016. Last accessed 21/7/2018

Accounting for the ‘Othello error’ is one reason a full ‘Outliar’ analysis uses an additional measure of language change within a text – intratextual language variation – when assessing text veracity. Texts can range from having a uniform style with consistent use of features throughout – a stable text – to displaying marked changes in language style at several points – variable or ‘spiky’ text.  Outliar captures this by summing the amount of change shown in a text.

Figure 5 is an example of this. It compares ‘Outliar’ analysis of Sharapova’s Facebook post (left) one of a Lance Armstrong TV interview in whch he falsely denied doping (see previous blog for more discussion of Armstrong’s deception). Visually, you can see that  Lance Armstrong’s language use displayes high variability in comparison to which Sharapova’s language is relatively stable.

Figure 5: Comparison of the ‘Outliar’ analysis of Maria Sharapova’s Facebook post (left) and Lance Armstrong’s ESPN interview (right) .

Figure 6 below shows a statistical measure of intratextual language variation for five false doping denials vs. five true doping confessions (see p7 here for the formula). It can be seen that the deceptive communications show more language change than the honest ones. So, combining outlier text detection with an overall measure of language variability can be helpful in distinguishing honesty from dishonesty. Frequent and marked language style change is a signal of potential deception.

intratext analysis edit 2

Figure 6: Analysis of intratextual variation. Y-axis = total intratextual variation measured as aggregate z-score for each text; X-axis represents ten texts in total –  five deceptive texts (false denials by: 1) Barry Bonds; 2) Linford Christie; 3) Lance Armstrong; 4) Alex Rodriguez; 5) Marion Jones) and five honest texts (true confessions by: 1) Maria Sharapova; 2) Dwain Chambers; 3) Victor Conte; 4) Floyd Landis; 5) Levi Leiphemer)

In Sharapova’s case, the tribunal were satisfied she had not intended to cheat (although she was found to have also taken the drug to enhance her performance) and her relatively light ban (reduced from two years to 15 months on appeal) reflected the fact that she had been negligent but not deceptive. I would argue that the (relatively) stable language of both Sharapova’s Facebook post and the initial press conference where she announced her drug test failure support the tribunal finding. The press conference video is below – judge for yourself.



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