Replication Data for the paper ‘Authenticity and personal signals increase hiring chances in online labor markets: large-scale analysis of online impression management’https://hdl.handle.net/21.15109/ARP/0XAKYAIlyés, VirágO’Szabo, RebekaCsászár, OlgaLászló, LőrinczARP2026-03-302026-03-30T11:56:34ZThe dataset was collected from Freelancer.com to examine how online impression management shapes hiring outcomes in gig-economy environments. It combines detailed information from project pages and freelancer profile pages to construct a linked project–applicant–level dataset. The data include rich information on project requirements, applicant bids, skills, reputation, and demographic proxies, as well as extensive textual features derived from application messages and personal introductions. These textual measures capture multiple dimensions of self-presentation, including structure, readability, formality, politeness strategies, sentiment, emotional tone, and persuasive language, alongside indicators of authenticity such as text uniqueness and introduction style. The primary goal of data collection is to provide large-scale empirical evidence on whether and how online self-presentation—beyond traditional “hard” signals like skills and experience—affects hiring decisions, and to identify which impression management strategies are rewarded or penalized across different types of work in online labor markets.Social Sciencesonline labor marketshiring outcomesself-presentationimpression managementjob applicationskillstext analysis2026-03-30Ilyés, Virág2026-03-25This dataset is made available for research purposes only. Users are free to use, share, and adapt the data for non-commercial research activities, provided that proper citation is given.Use of the dataset is limited to research purposes. Commercial use is not permitted without prior permission from the data provider.