Home

Menu

Loading wiki pages...

View
Wiki Version:
When and how to come out are difficult choices. In this research project, we examine one form of disclosure: the addition of an LGBTQ keyword to one's online social media profile. We construct daily time series of the prevalence of LGBTQ keywords within American Twitter users' self-descriptions. Further, we construct daily time series of inferred add and drop events. These we compare to relevant annual and one-time events. We confirm or disconfirm our pre-registered hypotheses. **Pre-Registered Hypotheses** On October 16, 2019, we finalized a list of LGBTQ-relevant events and a set of pre-registered hypotheses. We completed this before constructing the time-series datasets for this project. - [LGBTQ-relevant events][1] - [Pre-Registered Hypotheses][2] We uploaded [a manuscript][3] exploring these hypotheses on June 22, 2020. The [most recent manuscript][4] (uploaded Nov 20, 2020) contains more analysis. **Bostock Effect Pre-Registerd Hypotheses** Just after the Bostock US Supreme Court decision was announced, we created a new list of pre-registered hypotheses to explore: [Immediately Observable Effects (or not) of the Bostock US Supreme Court Decision on Personally Expressed LGBTQ Identity][5] [1]: https://osf.io/zc7qd/ [2]: https://osf.io/xrck2/ [3]: https://osf.io/dnbx3/ [4]: https://osf.io/preprints/socarxiv/8yjcm/ [5]: https://osf.io/v7ugw/
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
Accept
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.
Accept
×

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.