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Personal traits (BIG 5) and recruitment process

Hacker News

Personal traits (BIG 5) and recruitment process

I am trying to figure out whether there is any correlation between personal traits of a person (e.g. one's extraversion/introversion) and one's preferences towards recruitment process. It might be, in today's extraversion oriented world we might be missing something while creating recruitment processes. I am aiming particularly at IT sector. If you, the reader, what to learn something about yourself and are willing to help me in my study, make sure to take a look at the survey below: https://psychodpt.fra1.qualtrics.com/jfe/form/SV_3TTwu2qJgla... Total time of the study: 15-20 minutes.

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2comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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