mlsanityData to 14 Oct 2026

AI-enabled exploration of Instagram profiles predicts soft skills and personality traits to empower hiring decisions

arXiv 2212.07069 ↗First posted 14 Dec 2022cs.LG cs.CY cs.SIcited by 2

Not on the map. Why?

Abstract (arXiv)

It does not matter whether it is a job interview with Tech Giants, Wall Street firms, or a small startup; all candidates want to demonstrate their best selves or even present themselves better than they really are. Meanwhile, recruiters want to know the candidates' authentic selves and detect soft skills that prove an expert candidate would be a great fit in any company. Recruiters worldwide usually struggle to find employees with the highest level of these skills. Digital footprints can assist recruiters in this process by providing candidates' unique set of online activities, while social media delivers one of the largest digital footprints to track people. In this study, for the first time, we show that a wide range of behavioral competencies consisting of 16 in-demand soft skills can be automatically predicted from Instagram profiles based on the following lists and other quantitative features using machine learning algorithms. We also provide predictions on Big Five personality traits. Models were built based on a sample of 400 Iranian volunteer users who answered an online questionnaire and provided their Instagram usernames which allowed us to crawl the public profiles. We applied several machine learning algorithms to the uniformed data. Deep learning models mostly outperformed by demonstrating 70% and 69% average Accuracy in two-level and three-level classifications respectively. Creating a large pool of people with the highest level of soft skills, and making more accurate evaluations of job candidates is possible with the application of AI on social media user-generated data.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 73 references that are in the map. First posted on arXiv 14 Dec 2022.

Builds on

3 of 73 references.

References · 3

  1. 2015A Random Forest Guided Tourcited by 168
  2. 2019Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patternscited by 14
  3. 2022FETA: Fairness Enforced Verifying, Training, and Predicting Algorithms for Neural Networkscited by 4

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 1.

2 papers.