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Content Analysis of Unsolicited Emails as the Tool to Acquire Challenging Data: The Case of Using Semiquantitative Linguistic Analysis in Mining Unstructured Data

By: Published: 2020 | Product: SAGE Research Methods Cases: Medicine and Health
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Addressing some research questions requires access to the information that is not readily available because of privacy concerns or trade secrets. Employment data belong to this category due to issues related to competition, confidentiality, and marketing. At the center of this case, I used unsolicited recruitment emails containing some details of job offers to extract the data about conditions offered to potential anesthesiologists while applying for locum tenens positions. Specifically, elements of semiquantitive linguistic analysis were employed. Critical problems included low yield of information per email, creation of a robust database to capture information, external validation of data, and manuscript publication. The presented methodology can be applied to future research to uncover information helpful for job mobility and wage growth.

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