The inner quality of an article: Will time tell?

Chan, Ho Fai; Guillot, Malka; Page, Lionel; Torgler, Benno

doi:10.1007/s11192-015-1581-y

Cited by 8 publications

(5 citation statements)

References 57 publications

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“…The effect of changing writing style in terms of text length is well investigated in various disciplines. For example, various studies in the informetrics and scientometrics literature report a significantly positive relation between scientific article length and citation outcome (see [ 6 ], [ 7 ], [ 8 ], [ 9 ], [ 10 ]). On the other hand, short and succinct abstracts are more likely to increase citations than longer abstracts [ 11 ].…”

Section: Text Length and Informationmentioning

confidence: 99%

How much is too much? The effects of information quantity on crowdfunding performance

2018

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We explore the effects of the quantity of information on the tendency to contribute to crowdfunding campaigns. Using the crowdfunding platform Kickstarter, we analyze the campaign descriptions and the performance of over 70,000 projects. We look empirically at the effect of information quantity (word count) on funding success (as measure by amount raised and number of backers). Within this empirical approach, we test whether an excessive amount of information will affect funding success. To do so, we test for the non-linearity (quadratic) effect of our independent variable (word count) using regression analysis. Consistent with the hypothesis that excess information will negatively affect funds raised and number of contributors, we observe a consistent U-shaped relationship between campaign text length and overall success which suggest that an optimal number of words exists within crowdfunding texts and that going over this point will reduce a project’s chance of fundraising success.

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Section: Text Length and Informationmentioning

confidence: 99%

How much is too much? The effects of information quantity on crowdfunding performance

2018

Self Cite

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“…The peer-review process remains critical in preventing unworthy papers from being published even if they cite a large number of key papers. Chan et al (2015) note that the quality of the scientific contribution of a work can be biased due to factors such as institutional affiliation and the time of publication. Therefore, the eigenvector centrality metric identifies papers that are reachable from other key papers, but it does not serve as an absolute metric on the quality of identified Big Fish papers.…”

Section: Discussionmentioning

confidence: 99%

Identifying key papers within a journal via network centrality measures

et al. 2016

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This article examines the extent to which existing network centrality measures can be used (1) as filters to identify a set of papers to start reading within a journal and (2) as article-level metrics to identify the relative importance of a paper within a journal. We represent a dataset of published papers in the Public Library of Science (PLOS) via a cocitation network and compute three established centrality metrics for each paper in the network: closeness, betweenness, and eigenvector. Our results show that the network of papers in a journal is scale-free and that eigenvector centrality (1) is an effective filter and article-level metric and (2) correlates well with citation counts within a given journal. However, closeness centrality is a poor filter because articles fit within a small range of citations. We also show that betweenness centrality is a poor filter for journals with a narrow focus and a good filter for multidisciplinary journals where communities of papers can be identified.

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“…Of course, the geography and quality of institutions are related as most prestigious institutions are either in North America or Europe. Chan et al (2015) find that authors from high-ranking institutions get more citations for their Econometrica and AER publications, and Amara et al (2015) find that authors from high-ranking Canadian business schools receive more citations than authors from low-ranking Canadian business schools. However, authors from top institutions do not necessarily receive more citations in all academic fields.…”

Section: Related Literaturementioning

confidence: 97%

Predicting the impact of American Economic Review articles by author characteristics

Yuret

2022

Quantitative Science Studies

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Authors who publish in American Economic Review (AER) have career paths confined to a few prestigious institutions, and they mostly have exceptional past publication performance. In this paper, we show that authors who are educated and work in the top ten institutions and have better past publication performance receive more citations for their current AER publications. Authors who have published in the top economic theory journals receive fewer citations even after controlling for the subfield of their AER article. The gender of the authors, years of post-PhD experience, and the location of the affiliated institution do not have any significant effect on the citation performance. An opportunistic editor can exploit the factors that are related to citation performance to substantially improve the citation performance of the journal. Such an opportunistic behavior increases the over-representation of authors with certain characteristics. For example, the opportunistic editor who uses the predicted citation performance of articles to select a quarter of the articles increases the ratio of authors who works at the top ten institutions from 30.8 percent to 52.0 percent. Peer Review https://publons.com/publon/10.1162/qss_a_00180

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The inner quality of an article: Will time tell?

Cited by 8 publications

References 57 publications

How much is too much? The effects of information quantity on crowdfunding performance

How much is too much? The effects of information quantity on crowdfunding performance

Identifying key papers within a journal via network centrality measures

Predicting the impact of American Economic Review articles by author characteristics

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