新颖性
受众测量
出版
相似性(几何)
面子(社会学概念)
计算机科学
数据科学
社会学
情报检索
社会科学
政治学
业务
心理学
人工智能
广告
法学
图像(数学)
社会心理学
作者
Rui Dai,Lawrence Donohue,Qingyi Song Drechsler,Wei Jiang
出处
期刊:Review of Finance
[Oxford University Press]
日期:2022-03-16
卷期号:27 (1): 79-141
被引量:13
摘要
Abstract Using numeric and textual data extracted from over 50,000 finance articles in Social Science Research Network (SSRN) during 2001–19, we examine the relationship between measured qualities and a paper’s readership, eventual outlet, and impact. Conventionality (semantic similarity with existent research) helps boost readership and publication prospects. However, novelty in the forms of emerging topics and databases are associated with better publishing outcomes. Studies that do not easily map into established finance subfields or that introduce nonfinance elements face a higher hurdle. Finally, papers whose research questions span multiple fields are a hard sell, but those building on prior knowledge from multiple fields are valued.
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