Poincare: Recommending Publication Venues via Treatment Effect Estimation

by   Ryoma Sato, et al.

Choosing a publication venue for an academic paper is a crucial step in the research process. However, in many cases, decisions are based on the experience of researchers, which often leads to suboptimal results. Although some existing methods recommend publication venues, they just recommend venues where a paper is likely to be published. In this study, we aim to recommend publication venues from a different perspective. We estimate the number of citations a paper will receive if the paper is published in each venue and recommend the venue where the paper has the most potential impact. However, there are two challenges to this task. First, a paper is published in only one venue, and thus, we cannot observe the number of citations the paper would receive if the paper were published in another venue. Secondly, the contents of a paper and the publication venue are not statistically independent; that is, there exist selection biases in choosing publication venues. In this paper, we propose to use a causal inference method to estimate the treatment effects of choosing a publication venue effectively and to recommend venues based on the potential influence of papers.


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