{"id":5858,"date":"2023-05-10T06:41:38","date_gmt":"2023-05-10T06:41:38","guid":{"rendered":"https:\/\/researcher.life\/blog\/?p=5858"},"modified":"2024-02-19T06:30:33","modified_gmt":"2024-02-19T06:30:33","slug":"research-recommendations","status":"publish","type":"post","link":"https:\/\/researcher.life\/blog\/article\/research-recommendations\/","title":{"rendered":"Research Recommendations: R Discovery introduces Reading Lists from the Researcher Community"},"content":{"rendered":"
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As a researcher, one of the best things you can get is <\/span>research recommendations<\/span> 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 <\/span>study published by Renew Consultants<\/span>,<\/span><\/i> around 20%-30% of the articles accessed by researchers in 2021 came through <\/span>research recommendations<\/span> via email or on a social media account.1<\/sup><\/span> 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.\u00a0<\/span>\u00a0<\/span><\/p>\n However, following multiple individuals across various social media platforms and spending time tracking their posts for <\/span>research recommendations<\/span> 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<\/sup><\/span>\u00a0<\/span>Being dependent on a few sources and finite number of people for their <\/span>research recommendations<\/span> only adds to the challenge of discovering relevant content.<\/span>\u00a0<\/span><\/p>\n At R Discovery, we realized the importance of user-generated <\/a><\/span>research recommendations<\/span><\/a> and saw how researchers could benefit from the efforts of peers working in similar subject areas. But we also know that every researcher\u2019s 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 <\/span>research<\/span> recommendations<\/span> from their peers by leveraging our robust recommendations capabilities.<\/span>\u00a0<\/span><\/p>\n