What drives citations of frontier application publications?

Djokoto, Justice G.; Agyei-Henaku, Kofi Aaron A-O.; Afrane-Arthur, Akua A.; Badu-Prah, Charlotte; Gidiglo, Ferguson K.; Srofenyoh, Francis

doi:10.1016/j.heliyon.2020.e05428

Cited by 5 publications

(1 citation statement)

References 107 publications

(215 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is worth noting that we limited the inputs to in‐text citation count from different structural functions at

t_{r_{1} %}

(independent variables) and time (control variable), to keep the problem definition simple and general. Previous studies show that a linear model is an effective method for citation count prediction and feature selection analysis (Abramo et al, 2019; Djokoto et al, 2020; Jimenez et al, 2020; Yu et al, 2014). Therefore, we employed a linear model and analyzed the relative weights of regressors (i.e.,

w_{i}

), which quantitively gauges the effect of independent variables on the dependent variable.…”

Section: Methodsmentioning

confidence: 99%

Disclosing the relationship between citation structure and future impact of a publication

Huang

Qian

Huang

et al. 2021

Asso for Info Science & Tech

View full text Add to dashboard Cite

Each section header of an article has its distinct communicative function. Citations from distinct sections may be different regarding citing motivation. In this paper, we grouped section headers with similar functions as a structural function and defined the distribution of citations from structural functions for a paper as its citation structure. We aim to explore the relationship between citation structure and the future impact of a publication and disclose the relative importance among citations from different structural functions. Specifically, we proposed two citation counting methods and a citation life cycle identification method, by which the regression data were built. Subsequently, we employed a ridge regression model to predict the future impact of the paper and analyzed the relative weights of regressors. Based on documents collected from the Association for Computational Linguistics Anthology website, our empirical experiments disclosed that functional structure features improve the prediction accuracy of citation count prediction and that there exist differences among citations from different structural functions. Specifically, at the early stage of citation lifetime, citations from Introduction and Method are particularly important for perceiving future impact of papers, and citations from Result and Conclusion are also vital. However, early accumulation of citations from the Background seems less important.

show abstract

“…It is worth noting that we limited the inputs to in‐text citation count from different structural functions at

t_{r_{1} %}

w_{i}

), which quantitively gauges the effect of independent variables on the dependent variable.…”

Section: Methodsmentioning

confidence: 99%

Disclosing the relationship between citation structure and future impact of a publication

Huang

Qian

Huang

et al. 2021

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

Fine-grained citation count prediction via a transformer-based model with among-attention mechanism

Huang

et al. 2022

Information Processing & Management

View full text Add to dashboard Cite

Cyber-bullying research in Kenya: a meta-analysis

Kwanya

Kogos

Kibe

et al. 2021

GKMC

View full text Add to dashboard Cite

Purpose Cyber-bullying is a form of harassment that is perpetrated using electronic media. The practice has become increasingly common especially with the growing ubiquity of social media platforms. Most cyber-bullying cases inevitably occur on Facebook because it is the most preferred social media platform. However, little is known about cyber-bullying research in Kenya. This paper aims to analyse the quantity, quality, visibility and authorship trends of scholarly publications on cyber-bullying from and/or about Kenya. Design/methodology/approach This study was conducted as a systematic literature review. A meta-analysis approach was used. Bibliometrics approaches were used to conduct the analysis. Data on the publications was collected from Google Scholar using Harzing's “Publish or Perish” software and then analysed and presented using Microsoft Excel, Notepad and VOSviewer. Findings The study yielded 359 research publications on cyber-bullying in Kenya. There was a gradual increment in the number of publications, peaking in 2018. Nearly half of the publications have not been cited indicating low uptake of research on cyber-bullying in Kenya. It also emerged that most of the research has been published on subscription channels thereby restricting their visibility, access and use. Minimal collaboration in research on cyber-bullying in Kenya was also observed since 67.4% of the publications were written by a single (one) author. The authors conclude that the quantity, quality and visibility of research on cyber-bullying in Kenya is low. Originality/value This is an empirical study. The findings can be used to promote and mainstream research on cyber-bullying in Kenya.

show abstract

What drives citations of frontier application publications?

Cited by 5 publications

References 107 publications

Disclosing the relationship between citation structure and future impact of a publication

Disclosing the relationship between citation structure and future impact of a publication

Fine-grained citation count prediction via a transformer-based model with among-attention mechanism

Cyber-bullying research in Kenya: a meta-analysis

Contact Info

Product

Resources

About