Dissemination of knowledge is important to both the creator and the audience, who can benefit from access to new information. The scholarly impact of research can be measured through various means, including searching indexes, examining citations, and viewing social media. Profiling sites (such as LinkedIn and Experts@Syracuse) as well as institutional (e.g. SURFACE) and professional open repositories are important tools for increasing impact. This guide is designed to help you understand the methods and tools available for documenting and increasing scholarly impact.
Journal, book, article, and author-level metrics tabs explain what these are, how to calculate or find them, and highlight the tools at your disposal in order to do so.
Altmetrics are a means of measuring a scholar's impact based on their presence in the social web using online tools and environments.
OA is is the free, immediate, online availability of research articles coupled with the rights to use these articles fully in the digital environment. This ensures access to research, allows the authors to retain some or all of copyright ownership, and contributes to the social good by stimulating ideas, enriching education, and affecting policy development.
Profiling tools, like Experts@Syracuse, can influence or amplify scholarly impact through social networks and institutional reach.
This self-paced program has been designed to provide you with bite-sized assignments to help you navigate the tools and synthesize these indicators of activity, dissemination, and conversation around your work. Syracuse University Libraries will introduce you to the tools that can amplify your expertise, promote your research online, find funding and collaborators, and discover the conversations or engagement happening around your area of specialty.
Citation analysis is a quantifiable measure of academic output. Users need to be aware of the limitations and incongruities of citation metrics. Library subscription databases and Google Scholar do not correct errors in citing papers. This means that one paper may be cited many different ways and appear as separate entries in these tools. Also, author and institutional naming inconsistencies complicate these analyses. Comparisons between these tools should be avoided. The databases use different sources to generate data and some are more comprehensive than others.