Replication Data for the paper ‘Authenticity and personal signals increase hiring chances in online labor markets: large-scale analysis of online impression management’hdl:21.15109/ARP/0XAKYAARP2026-03-301Ilyés, Virág; O’Szabo, Rebeka; Császár, Olga; László, Lőrincz, 2026, "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/0XAKYA, ARP, V1Replication Data for the paper ‘Authenticity and personal signals increase hiring chances in online labor markets: large-scale analysis of online impression management’hdl:21.15109/ARP/0XAKYAIlyés, VirágO’Szabo, RebekaCsászár, OlgaLászló, LőrinczIlyés, VirágARPIlyés, VirágIlyés, Virág2026-03-25Social Sciencesonline labor marketshiring outcomesself-presentationimpression managementjob applicationskillstext analysisThe 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.The dataset does not contain personal or confidential information to the best of the authors’ knowledge.No special permissions are required beyond compliance with the stated terms of use.Use of the dataset is limited to research purposes. Commercial use is not permitted without prior permission from the data provider.Users must cite the dataset in any publication or output using it. Proper citation should include the dataset title, authors, year, and repository.Users must not misrepresent the data or its source.By using this dataset, users agree to comply with these terms and conditions.The dataset is provided "as is" without warranty of any kind. The authors are not responsible for any errors or for any consequences arising from the use of the data.This 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.Contact for Access: ilyes.virag@krtk.elte.hu ilyesvirag@gmail.com Terms of Access for Restricted Files: Access to the data is granted for research purposes upon request. Users must agree to cite the dataset appropriately.codebook.xlsxVariable-level documentation with names, descriptions, and variable typesapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheetcustom_dictionaries.docxDetailed description of the custom dictionaries used for feature extractionapplication/vnd.openxmlformats-officedocument.wordprocessingml.documentdata_full.csvCleaned dataset used for the analysis, including all variables described in the codebooktext/csvdocumentation.docxComprehensive documentation covering data collection, methodology, and dataset structureapplication/vnd.openxmlformats-officedocument.wordprocessingml.document