Text and Team: What Article Metadata Characteristics Drive Citations in Software Engineering?
Lorenz Graf-Vlachy, Daniel Graziotin, Stefan Wagner

TL;DR
This study investigates how article metadata characteristics like title, abstract, keywords, and authors influence citation counts in software engineering, using regression analysis on a large dataset of publications.
Contribution
It proposes a theoretical model linking metadata features to citations and empirically tests these hypotheses with extensive data, revealing significant correlations.
Findings
Number of authors correlates with higher citations.
More keywords and question marks in titles increase citation likelihood.
Abstract length and propositional density are positively related to citations.
Abstract
Context: Citations are a key measure of scientific performance in most fields, including software engineering. However, there is limited research that studies which characteristics of articles' metadata (title, abstract, keywords, and author list) are driving citations in this field. Objective: In this study, we propose a simple theoretical model for how citations come to be with respect to article metadata, we hypothesize theoretical linkages between metadata characteristics and citations of articles, and we empirically test these hypotheses. Method: We use multiple regression analyses to examine a data set comprising the titles, abstracts, keywords, and authors of 16,131 software engineering articles published between 1990 and 2020 in 20 highly influential software engineering venues. Results: We find that number of authors, number of keywords, number of question marks and dividers in…
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