> The participants described the first few individuals quite positively, using an average of 6.2 positive words each. But as they progressed through the sequence, their descriptions became significantly more negative, dipping to an average of just 4.7 positive words by the 20th person.
I don't have access to the study, but I'd be curious why they chose to count positive words as opposed to just asking people to rate on a numerical scale? My impression is that sentiment scoring via bag-of-words is not a particularly robust method, especially in 2024. It also sounds like they didn't normalize by description length, so outcome could just as easily be because people's responses got shorter as time went on due to fatigue?
(also, this is a nit with the article rather than the study, but given the methodology I think it is important to distinguish between becoming less positive and becoming more negative, and in this case I would not describe using fewer positive words as "became significantly more negative")
Yeah - antidotally I feel like earlier in a hiring process people are apt to expound on candidates fit for portions of the role and in later stages it basically just thumbs up or down and only more exposition in the case of disagreement
Yeah, when you don't have anything to compare them with you need to describe them. But once you have some strong candidates to compare them with everyone just becomes "are they better or worse than X".
I'd imagine this is tricky. Today everyone in white collar culture is so guarded with language so as not to offend. You have to have an extremely sensitive ear to understand that mildly positive words actually mean extremely negative.
I'd really need to see this study reproduced several times before I take it seriously at all. Ideally there'd also be other similar but non-identical studies pointing to the same effect.
I don't think any of the common problems[1] are relevant for this specific application (understanding the importance of serial position). Like I said, I'd be curious to understand the motivation behind their methodology choice.
I don't have access to the study, but I'd be curious why they chose to count positive words as opposed to just asking people to rate on a numerical scale? My impression is that sentiment scoring via bag-of-words is not a particularly robust method, especially in 2024. It also sounds like they didn't normalize by description length, so outcome could just as easily be because people's responses got shorter as time went on due to fatigue?
(also, this is a nit with the article rather than the study, but given the methodology I think it is important to distinguish between becoming less positive and becoming more negative, and in this case I would not describe using fewer positive words as "became significantly more negative")