As a researcher, one of the best things you can get is research recommendations from peers and experts in your field. In fact, researchers often follow their peers or established authors on social media platforms such as Twitter or LinkedIn to read the papers they share or speak about. As per a study published by Renew Consultants, around 20%-30% of the articles accessed by researchers in 2021 came through research recommendations via email or on a social media account.1 These recommendations are invaluable as they help researchers stay up to date on the latest findings in their area of research while saving time in their own literature discovery process.
However, following multiple individuals across various social media platforms and spending time tracking their posts for research recommendations can be very cumbersome. As per a study by Elsevier, researchers spend an equal amount of time searching for scholarly articles as reading them and 50% of the articles they did read were irrelevant. 2 Being dependent on a few sources and finite number of people for their research recommendations only adds to the challenge of discovering relevant content.
At R Discovery, we realized the importance of user-generated research recommendations and saw how researchers could benefit from the efforts of peers working in similar subject areas. But we also know that every researcher’s style of content discovery is very different, hence, the reading lists curated by individuals can vary drastically. So, we worked toward resolving this pain point by empowering researchers to discover research recommendations from their peers by leveraging our robust recommendations capabilities.
Introducing Reading Lists from the Researcher Community
R Discovery’s powerful AI-based recommendations system allows researchers to discover relevant scholarly articles and save them as separate lists. With our latest Reading Lists from the Researcher Community feature, users will be able to make their lists public and discoverable to other users, which enables quick and easy discovery of community-generated research recommendations. This enhances the research reading experience for R Discovery users by opening up a different path for content discovery, in addition to their own personalized reading lists.
To discover more such shared research recommendations and see Reading Lists from the Researcher Community, users need to make at least one of their own reading lists public. There’s a very simple way to do this – just click on the Edit feature for your reading lists and use the Private-Public toggle to set your preference.
Not only are the community-generated lists of research recommendations visible to R Discovery users, those who own these reading lists will also be able to forward them externally to their own teams, collaborators, and peers.
Community-generated lists enable faster research discovery
On R Discovery, users select their preferred topics of interest which our system then uses to browse the more than 100 million papers in our repository and recommend the latest, most relevant articles for them to read. The addition of Reading Lists from the Researcher Community now allows us to also match a user’s preferred topics to the most relevant research recommendation lists created by peers on the vertical feed. This enables users to further speed up the literature discovery process with access to handpicked research articles on specific topics collated within a single reading list.
How to find Reading Lists from the Researcher Community
R Discovery users will not only be able to view research recommendations in community-generated reading lists, but they can also save the research papers they find most relevant to their own lists and library.
Researchers can even follow chosen Reading Lists from the Researcher Community to learn when the owner adds articles or changes access to the list. The best part is that R Discovery lets users share these specially curated reading lists with peers or on social media platforms!
Community research recommendations open the door for new collaborations
With Reading Lists from the Researcher Community, we aim to help researchers discover content curated by peers in the same research field. Going forward, we are also working on finding ways to help researchers connect with peers to discuss new potential research and future collaborations.
As we continue our work to making your experience better, we would love to hear from you about what we should build next to make your literature discovery process better. Email us and we’ll set up a quick chat or simply share feedback on the new Reading Lists from the Researcher Community feature at discovery@researcher.life.
If you haven’t used R Discovery yet, this is your chance to get relevant research recommendations and simplify your research discovery. Click to install the free R Discovery app now!
References:
- Gardner T., Inger S. How Readers Discover Content in Scholarly Publications. Renew Consultants, July 2021. Available at https://renewconsultants.com/wp-content/uploads/2021/07/How-Readers-Discover-Content-2021.pdf
- Trust in Research. Research Survey by Elsevier and Sense About Science, June 2019. Available at https://www.elsevier.com/__data/assets/pdf_file/0011/908435/Trust_evidence_report_summary_Final.pdf
