Past, Present, and Future of Citation Practices in HCI
- URL: http://arxiv.org/abs/2405.16526v4
- Date: Tue, 10 Sep 2024 16:12:41 GMT
- Title: Past, Present, and Future of Citation Practices in HCI
- Authors: Jonas Oppenlaender,
- Abstract summary: We show how a change in editorial policies introduced at the ACM CHI Conference in 2016 launched the CHI community on an expansive path.
If this near-linear trend continues undisrupted, an article in CHI 2030 will include on average almost 130 references.
This article underscores the profound impact that meso-level policy adjustments have on the evolution of scientific fields and disciplines.
- Score: 5.498355194100662
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Science is a complex system comprised of many scientists who individually make collective decisions that, due to the size and nature of the academic system, largely do not affect the system as a whole. However, certain decisions at the meso-level of research communities, such as the Human-Computer Interaction (HCI) community, may result in deep and long-lasting behavioral changes in scientists. In this article, we provide evidence on how a change in editorial policies introduced at the ACM CHI Conference in 2016 launched the CHI community on an expansive path, denoted by a year-by-year increase in the mean number of references included in CHI articles. If this near-linear trend continues undisrupted, an article in CHI 2030 will include on average almost 130 references. The trend towards more citations reflects a citation culture where quantity is prioritized over quality, contributing to both author and peer reviewer fatigue. This article underscores the profound impact that meso-level policy adjustments have on the evolution of scientific fields and disciplines, urging stakeholders to carefully consider the broader implications of such changes.
Related papers
- From Words to Worth: Newborn Article Impact Prediction with LLM [69.41680520058418]
This paper introduces a promising approach, leveraging the capabilities of fine-tuned LLMs to predict the future impact of newborn articles.
A comprehensive dataset has been constructed and released for fine-tuning the LLM, containing over 12,000 entries with corresponding titles, abstracts, and TNCSI_SP.
arXiv Detail & Related papers (2024-08-07T17:52:02Z) - Mapping the Increasing Use of LLMs in Scientific Papers [99.67983375899719]
We conduct the first systematic, large-scale analysis across 950,965 papers published between January 2020 and February 2024 on the arXiv, bioRxiv, and Nature portfolio journals.
Our findings reveal a steady increase in LLM usage, with the largest and fastest growth observed in Computer Science papers.
arXiv Detail & Related papers (2024-04-01T17:45:15Z) - 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) - Regulation and NLP (RegNLP): Taming Large Language Models [51.41095330188972]
We argue how NLP research can benefit from proximity to regulatory studies and adjacent fields.
We advocate for the development of a new multidisciplinary research space on regulation and NLP.
arXiv Detail & Related papers (2023-10-09T09:22:40Z) - Uncited articles and their effect on the concentration of citations [0.0]
Empirical evidence shows that citations received by scholarly publications follow a pattern of preferential attachment, resulting in a power-law distribution.
Are citations becoming more concentrated in a small number of articles? Or have recent geopolitical and technical changes in science led to more decentralized distributions?
This article explores how reference-based and citation-based approaches, uncited articles, citation inflation, the expansion of bibliometric databases, disciplinary differences, and self-citations affect the evolution of citation concentration.
arXiv Detail & Related papers (2023-06-16T15:38:12Z) - Modeling Information Change in Science Communication with Semantically
Matched Paraphrases [50.67030449927206]
SPICED is the first paraphrase dataset of scientific findings annotated for degree of information change.
SPICED contains 6,000 scientific finding pairs extracted from news stories, social media discussions, and full texts of original papers.
Models trained on SPICED improve downstream performance on evidence retrieval for fact checking of real-world scientific claims.
arXiv Detail & Related papers (2022-10-24T07:44:38Z) - The Concept of Decentralization Through Time and Disciplines: A
Quantitative Exploration [0.0]
We analyse 425,144 academic publications that refer to (de)centralization.
We find that the fraction of papers on the topic has been exponentially increasing since the 1950s.
In 2021, 1 author in 154 mentioned (de)centralization in the title or abstract of an article.
arXiv Detail & Related papers (2022-07-28T17:46:46Z) - Fairness in Recommender Systems: Research Landscape and Future
Directions [119.67643184567623]
We review the concepts and notions of fairness that were put forward in the area in the recent past.
We present an overview of how research in this field is currently operationalized.
Overall, our analysis of recent works points to certain research gaps.
arXiv Detail & Related papers (2022-05-23T08:34:25Z) - Change Summarization of Diachronic Scholarly Paper Collections by
Semantic Evolution Analysis [10.554831859741851]
We demonstrate a novel approach to analyze the collections of research papers published over longer time periods.
Our approach is based on comparing word semantic representations over time and aims to support users in a better understanding of large domain-focused archives of scholarly publications.
arXiv Detail & Related papers (2021-12-07T11:15:19Z) - Evolving Methods for Evaluating and Disseminating Computing Research [4.0318506932466445]
Social and technical trends have significantly changed methods for evaluating and disseminating computing research.
Traditional venues for reviewing and publishing, such as conferences and journals, worked effectively in the past.
Many conferences have seen large increases in the number of submissions.
Dis dissemination of research ideas has become dramatically through publication venues such as arXiv.org and social media networks.
arXiv Detail & Related papers (2020-07-02T16:50:28Z)
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.