This post introduces you to initial user research on Steemit since joining back in October 2017. The research focuses on a sample of Steemit and the initial data is based on the months October to December 2017. This will help develop insights and identify recommendations to help improve the overall Steemit user experience. Research will be posted in a few instalments rather than bombarding you with too much information at once. Your feedback is welcome.
Initial search
The process of understanding Steemit photographers started with a thorough search of photography subjects. Examples of photography search terms included; portrait, still life, travel, food, fashion, glamour and music. Photographers appearing within these search terms were listed in the table below and analysed in more detail. The initial search also identified several third-party photographer sites built on the Steemit blockchain, such as Steepshot and Bescouted. Both sites presented photographers with high-quality images which will be investigated further.
Search functionality limited
One of the difficulties I experienced involved using the search function. It’s quite basic and limited without scope for a more advanced search option. I was unable to search for photographers within a specified date range. While I recognise Steemit caters for a variety of users, an option to search for popular users under different categories, such as a ‘top ten photographer’ might have helped. The search function returns results based on embedding a maximum five tags per post which has its limitations.
As you can see in the table, several photographers specialise in travel, food, portrait, nature or landscape photography. I added photographers from various fields including 
Measuring Quality
Image quality was as varied as the subject matter. One of the photographers, 
Identifying photographers with a similar standard of quality images will assist developing personas which will help understand photographer user needs. I acknowledge judging a photographic image quality is subjective partly because it’s a case of ‘Beauty is in the eye of the beholder’. A search of academic journals also confirmed measuring image quality is difficult because judging photograph aesthetics is subjective in nature (Datta, Joshi, Li, & Wang, 2006). Research identified an alternative community-reviewed rating system might work, such as photo.net, where other users can rate photographer’s images online (Datta et al., 2006).
What’s Next?
Steemit has the capability to use various metrics to assist measuring image quality such as the number of votes an image attracts or possibly the value of an image posted on Steemit. Further research is needed to understand the relationship between votes for an image posted on Steemit, versus the overall value an image generates. The question will be whether this is a reliable basis for measuring image quality or if this metric serves any useful purpose. Future user research will hopefully identify the steps you can take to increase image value.
I would like to thank 
Datta, R., Joshi, D., Li, J., & Wang, J. Z. (2006). Studying Aesthetics in Photographic Images Using a Computational Approach, Berlin, Heidelberg.