Paper short abstract:

Instagram Stories, lasting only 24-hours, are a ‘safe’ means of documenting experiences of dating apps in Dhaka: bad dates, ghosting and rejection. To contend with ethical ramifications, we conducted a review of existing ethical frameworks on online participant observation to be adapted for our use.

Paper long abstract:

In the Bangladeshi context, discourse around dating exists in a delicate balance between the desire for love and romance, against ideas of respectability shaped through religio-cultural norms and practices. Instagram and other social media can be a ‘safe’ space to post their experiences and frustrations of using online dating applications in Dhaka, Bangladesh such as: underwhelming dates and experiences of ‘ghosting’ and rejection. Particularly, Instagram Stories (lasting only 24 hours) are an extremely private medium due to its ephemeral nature, but ethical data collection was difficult to justify as a result.

Our methodology aimed to shift away from the so-called ‘big data revolution’ and identify meaningful mechanisms to collect ‘small data’ (boyd and Crawford, 2012), that captured the rich, contextual meaning making process in the sharing-resharing of memes, reels, and personal musings, while circumventing the culture of silence and public secrecy around dating.

We review and analyze ethical frameworks created by the Internet Research: Ethical Guidelines 3.0 (Association of Internet Researchers, 2019); Latzko-Toth, Bonneau, and Millette (2016) on thickening data; and Uberti (2021) on the ethics of internet-mediated research and ‘lurking’. We combine these with literature on reflexivity and positionality of the researcher as an insider, particularly considering that the 15 participants approached for interviews were determined through convenience sampling, and therefore known to the researchers from before, due to the nature of secrecy around dating and relationships in our cultural context. Through this, we were able to design our own adapted ethical framework to collect rich, ethnographic digital data.