3 ms·

> ... a linguistic analysis of real-life social interactions on Facebook ... How can they tell if people are being dishonest on Facebook?

by asaph 7y ago

sethammons 7y ago
yeah, agreed. I would have thought it would be on the recipient/observer to report if they thought it was a a truthy or falsey statement, but the snippet above does not say that.
- asaph 7y ago
  Even if the researchers fact check Facebook posts and found them to be untrue, that still wouldn't conclusively point to dishonesty because the message poster might believe in the falsehood. It's not a lie if you believe it.
  - deleted 7y ago
    [deleted]
throwaway287391 7y ago
> The honesty of the status updates written by the participants was assessed following the approach introduced by Newman, Pennebaker, Berry, and Richards (2003) using LIWC. Their analyses showed that liars use fewer first-person pronouns (e.g., I, me), fewer third-person pronouns (e.g., she, their), fewer exclusive words (e.g., but, exclude), more motion verbs (e.g., arrive, go), and more negative words (e.g., worried, fearful; Newman, Pennebaker, Berry, & Richards, 2003). The explanation was that dishonest people subconsciously try to (1) dissociate themselves from the lie and therefore refrain from referring to themselves, (2) prefer concrete over abstract language when referring to others (using someone’s name instead of “he” or “she”), (3) are likely to feel discomfort by lying and therefore express more negative feelings, and (4) require more mental resources to obscure the lie and therefore end up using less cognitively demanding language, which is characterized by a lower frequency of exclusive words and a higher frequency of motion verbs. Equation and usage rates in this study are summarized in Table 2. > Newman et al. (2003) achieved up to 67% accuracy when detecting lies, which was significantly higher than the 52% near-chance accuracy achieved by human judges. Their approach has been successfully applied to behavioral data (Slatcher et al., 2007) and to Facebook status updates (Feldman, Chao, Farh, & Bardi, 2015). Other studies have since found support for these LIWC dimensions as being indicative of lying and dishonesty (Bond & Lee, 2005; Hancock, Curry, Goorha, & Woodworth, 2007; see meta-analyses by DePaulo et al., 2003 and Hauch, Masip, Blandón-Gitlin, & Sporer, 2012). So it's all purely from linguistic analysis of the status updates. Seems like a stretch to me but I wouldn't doubt the overall result is true.
- asaph 7y ago
  Thank you for finding the details of the methodology. I find this unconvincing. 67% accuracy, while better than a coin flip, is still pretty low. 1/3rd of their data points on the relationship between dishonesty and profanity on Facebook are wrong by their own admission.
blattimwind 7y ago
> real-life social interactions on Facebook oxymoron

> ... a linguistic analysis of real-life social interactions on Facebook ... How can they tell if people are being dishonest on Facebook?

by asaph 7y ago

> ... a linguistic analysis of real-life social interactions on Facebook ... How can they tell if people are being dishonest on Facebook?

sethammons 7y ago

yeah, agreed. I would have thought it would be on the recipient/observer to report if they thought it was a a truthy or falsey statement, but the snippet above does not say that.

asaph 7y ago
Even if the researchers fact check Facebook posts and found them to be untrue, that still wouldn't conclusively point to dishonesty because the message poster might believe in the falsehood. It's not a lie if you believe it.
- deleted 7y ago
  [deleted]

throwaway287391 7y ago

> The honesty of the status updates written by the participants was assessed following the approach introduced by Newman, Pennebaker, Berry, and Richards (2003) using LIWC. Their analyses showed that liars use fewer first-person pronouns (e.g., I, me), fewer third-person pronouns (e.g., she, their), fewer exclusive words (e.g., but, exclude), more motion verbs (e.g., arrive, go), and more negative words (e.g., worried, fearful; Newman, Pennebaker, Berry, & Richards, 2003). The explanation was that dishonest people subconsciously try to (1) dissociate themselves from the lie and therefore refrain from referring to themselves, (2) prefer concrete over abstract language when referring to others (using someone’s name instead of “he” or “she”), (3) are likely to feel discomfort by lying and therefore express more negative feelings, and (4) require more mental resources to obscure the lie and therefore end up using less cognitively demanding language, which is characterized by a lower frequency of exclusive words and a higher frequency of motion verbs. Equation and usage rates in this study are summarized in Table 2. > Newman et al. (2003) achieved up to 67% accuracy when detecting lies, which was significantly higher than the 52% near-chance accuracy achieved by human judges. Their approach has been successfully applied to behavioral data (Slatcher et al., 2007) and to Facebook status updates (Feldman, Chao, Farh, & Bardi, 2015). Other studies have since found support for these LIWC dimensions as being indicative of lying and dishonesty (Bond & Lee, 2005; Hancock, Curry, Goorha, & Woodworth, 2007; see meta-analyses by DePaulo et al., 2003 and Hauch, Masip, Blandón-Gitlin, & Sporer, 2012). So it's all purely from linguistic analysis of the status updates. Seems like a stretch to me but I wouldn't doubt the overall result is true.

asaph 7y ago
Thank you for finding the details of the methodology. I find this unconvincing. 67% accuracy, while better than a coin flip, is still pretty low. 1/3rd of their data points on the relationship between dishonesty and profanity on Facebook are wrong by their own admission.

blattimwind 7y ago

> real-life social interactions on Facebook oxymoron