Does the Venue of Scientific Conferences Leverage their Impact? A Large
Scale study on Computer Science Conferences
- URL: http://arxiv.org/abs/2105.14838v1
- Date: Mon, 31 May 2021 09:51:39 GMT
- Title: Does the Venue of Scientific Conferences Leverage their Impact? A Large
Scale study on Computer Science Conferences
- Authors: Luca Bedogni and Giacomo Cabri and Riccardo Martoglia and Francesco
Poggi
- Abstract summary: We conducted a large scale analysis on the data extracted from 3,838 Computer Science conference series and over 2.5 million papers spanning more than 30 years of research.
To quantify the "touristicity" of a venue we exploited some indicators such as the size of the Wikipedia page for the city hosting the venue and other indexes from reports of the World Economic Forum.
More-over the almost linear correlation with the Tourist Service Infrastructure index attests the specific importance of tourist/accommodation facilities in a given country.
- Score: 2.8388425545775386
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Background: Conferences bring scientists together and provide one of the most
timely means for disseminating new ideas and cutting-edge works.The importance
of conferences in scientific areas is testified by quantitative indicators. In
Computer Science, for instance, almost two out of three papers published on
Scopus are conference papers. Objective/Purpose: The main goal of this paper is
to investigate a novel research question: is there any correlation between the
impact of a scientific conference and the venue where it took place? Approach:
In order to measure the impact of conferences we conducted a large scale
analysis on the bibliographic data extracted from 3,838 Computer Science
conference series and over 2.5 million papers spanning more than 30 years of
research. To quantify the "touristicity" of a venue we exploited some
indicators such as the size of the Wikipedia page for the city hosting the
venue and other indexes from reports of the World Economic Forum.
Results/Findings: We found out that the two aspects are related, and the
correlation with conference impact is stronger when considering country-wide
touristic indicators, such as the Travel&Tourism Competitiveness Index.
More-over the almost linear correlation with the Tourist Service Infrastructure
index attests the specific importance of tourist/accommodation facilities in a
given country. Conclusions: This is the first attempt to focus on the
relationship of venue characteristics to conference papers. The results open up
new possibilities, such as allowing conference organizers and authors to
estimate in advance the impact of conferences, thus supporting them in their
decisions.
Related papers
- Position: AI/ML Influencers Have a Place in the Academic Process [82.2069685579588]
We investigate the role of social media influencers in enhancing the visibility of machine learning research.
We have compiled a comprehensive dataset of over 8,000 papers, spanning tweets from December 2018 to October 2023.
Our statistical and causal inference analysis reveals a significant increase in citations for papers endorsed by these influencers.
arXiv Detail & Related papers (2024-01-24T20:05:49Z) - COVID-19 Imposes Rethinking of Conferencing -- Environmental Impact
Assessment of Artificial Intelligence Conferences [0.0]
This is the first time that systematic quantification of a state-of-the-art subject like Artificial Intelligence takes place to define its conferencing footprint in the broader frames of environmental awareness.
Alternatives to optimal conferences' location selection have demonstrated savings on air-travelling CO2 emissions of up to 63.9%.
arXiv Detail & Related papers (2023-11-06T18:04:02Z) - CausalCite: A Causal Formulation of Paper Citations [80.82622421055734]
CausalCite is a new way to measure the significance of a paper by assessing the causal impact of the paper on its follow-up papers.
It is based on a novel causal inference method, TextMatch, which adapts the traditional matching framework to high-dimensional text embeddings.
We demonstrate the effectiveness of CausalCite on various criteria, such as high correlation with paper impact as reported by scientific experts.
arXiv Detail & Related papers (2023-11-05T23:09:39Z) - Estimating the Causal Effect of Early ArXiving on Paper Acceptance [56.538813945721685]
We estimate the effect of arXiving a paper before the reviewing period (early arXiving) on its acceptance to the conference.
Our results suggest that early arXiving may have a small effect on a paper's chances of acceptance.
arXiv Detail & Related papers (2023-06-24T07:45:38Z) - Analyzing the State of Computer Science Research with the DBLP Discovery
Dataset [0.0]
We conduct a scientometric analysis to uncover the implicit patterns hidden in CS metadata.
We introduce the CS-Insights system, an interactive web application to analyze CS publications with various dashboards, filters, and visualizations.
Both D3 and CS-Insights are open-access, and CS-Insights can be easily adapted to other datasets in the future.
arXiv Detail & Related papers (2022-12-01T16:27:42Z) - Twin Papers: A Simple Framework of Causal Inference for Citations via
Coupling [40.60905158071766]
The main difficulty in investigating the effects is that we need to know counterfactual results, which are not available in reality.
The proposed framework regards a pair of papers that cite each other as twins.
We investigate twin papers that adopted different decisions, observe the progress of the research impact brought by these studies, and estimate the effect of decisions by the difference.
arXiv Detail & Related papers (2022-08-21T10:42:33Z) - Learning to Drive on the Wrong Side of the Road: How American Computing
Came to Rely on Conferences for Primary Publication [1.0660480034605242]
This paper presents the first systematic investigation of the development of modern computing publications.
It relies on semi-structured interviews with eight computing professors from diverse backgrounds to understand how researchers experienced changes in publication culture over time.
arXiv Detail & Related papers (2021-09-14T04:59:09Z) - Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and
Conference Experiment Design [76.40919326501512]
We consider the question: how should reviewers be divided between phases or conditions in order to maximize total assignment similarity?
We empirically show that across several datasets pertaining to real conference data, dividing reviewers between phases/conditions uniformly at random allows an assignment that is nearly as good as the oracle optimal assignment.
arXiv Detail & Related papers (2021-08-13T19:29:41Z) - Industry and Academic Research in Computer Vision [5.634825161148484]
This work aims to study the dynamic between research in the industry and academia in computer vision.
The results are demonstrated on a set of top-5 vision conferences that are representative of the field.
arXiv Detail & Related papers (2021-07-10T20:09:52Z) - What's New? Summarizing Contributions in Scientific Literature [85.95906677964815]
We introduce a new task of disentangled paper summarization, which seeks to generate separate summaries for the paper contributions and the context of the work.
We extend the S2ORC corpus of academic articles by adding disentangled "contribution" and "context" reference labels.
We propose a comprehensive automatic evaluation protocol which reports the relevance, novelty, and disentanglement of generated outputs.
arXiv Detail & Related papers (2020-11-06T02:23:01Z) - A Hierarchical Network for Abstractive Meeting Summarization with
Cross-Domain Pretraining [52.11221075687124]
We propose a novel abstractive summary network that adapts to the meeting scenario.
We design a hierarchical structure to accommodate long meeting transcripts and a role vector to depict the difference among speakers.
Our model outperforms previous approaches in both automatic metrics and human evaluation.
arXiv Detail & Related papers (2020-04-04T21:00:41Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.