Conclusions

The availability of venue rankings is becoming a differential service in digital libraries and academic repositories. These rankings are generally produced in an attempt to capture or quantify the quality of each venue. By using these rankings, one could better understand the reputation of the venues he/she is interested in. Furthermore, understanding and quantifying the reputation of publication venues is an important tool for researchers, when deciding the most appropriate place to submit a paper, and for funding agencies, to track the productivity of researchers in order to make better decisions about their investments.

In this work, we discuss the applicability of a reputation-based method to quantify the reputation, or prestige, of publication venues. This method, called R-Score (for reputation-based scoring), relies on researchers and professors in institutions, groups, and departments of high reputation in a given area of knowledge. These researchers, which are distinguished individuals in their fields of knowledge, constitute sources of reference and reputation. Once they publish in a venue, they transfer part of their reputation to that venue.

R-Score depends neither on citations nor on document contents, relying solely on a set of top research groups in an area and on a list of all papers published by each group. Specifically, the reputation of the venues are inherited from a reference set composed by the top research groups in a given area. This fact makes R-Score much easier to compute in practice if compared with citation-based methods.

In here, we apply the proposed method to rank venues of three knowledge areas: Computer Science, Economics and Biochemistry. The rankings produced by R-Score were compared with rankings based on the well known Impact Factor, the most used citation-based metric to analyze venues. The results show that: (i) there is no need to choose more than 10 research groups if those are the top ones in the given area; (ii) if we trust only on IF, many important venues would be out of the analysis; (iii) there are interdisciplinary venues in top positions of the IF-based ranking even though these venues are clearly not among the most important venues in the given area. Even in the areas of Economics and Biochemistry, where the rankings based on Impact Factor seems to be more coherent (if compared with Computer Science), we could notice a coverage issue because there are not many venues with computed Impact Factor. These facts indicate that R-Score can be used to produce meaninful rankings without too much effort.