Data Extraction and Coding Challenges: Using Online Female Escort Advertisements to Test Evolutionary-Based Hypotheses

Abstract

This case provides an account of conducting a study that tested evolutionary-based predictions using online advertisements of female escorts. Its primary focus is on the identification and extraction of data, as well as issues involved with coding the data, and includes a summary of data analyses and findings. This study used publicly available online information that was coded into usable data for the purposes of testing evolutionary-based hypotheses. The subjects in this study were not actually humans but advertisements on characteristics associated with sex workers. The type of data that was collected for the study included age weight, height, waist and hip measurements, the fee for 1 hr of service, and photographs. There were considerable data-related obstacles to overcome during the course of the study which required a collaboration with several graduate students, a computer programmer, and myself (a psychologist), so this project required an interdisciplinary team. The challenges of conducting research on controversial topics and difficult-to-access populations are also discussed.

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