Scholarly events and venues are increasing rapidly in number. This poses a challenge for researchers who seek to identify events and venues related to their work in order to draw more efficiently and comprehensively from published research and to share their own findings more effectively. Such efforts are hampered also by the fact that no rating system yet exists to assist researchers in culling the venues most relevant to their current readings and interests. This study describes a methodology we developed in response to this need, one that recommends scholarly venues related to researchers’ specific interests according to personalized social web indicators. Our experiments applying our proposed rating and recommendation method show that it outperforms the baseline venue recommendations in terms of accuracy and ranking quality.