ReportAGE: Automatically extracting the exact age of Twitter users based on self-reports in tweets.

ABSTRACT: Advancing the utility of social media data for research applications requires methods for automatically detecting demographic information about social media study populations, including users' age. The objective of this study was to develop and evaluate a method that automatically identifies the exact age of users based on self-reports in their tweets. Our end-to-end automatic natural language processing (NLP) pipeline, ReportAGE, includes query patterns to retrieve tweets that potentially mention an age, a classifier to distinguish retrieved tweets that self-report the user's exact age ("age" tweets) and those that do not ("no age" tweets), and rule-based extraction to identify the age. To develop and evaluate ReportAGE, we manually annotated 11,000 tweets that matched the query patterns.

SUBMITTER: Klein AZ 

PROVIDER: S-EPMC8789116 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature