Attention decay in science
Not on the map. Why?
Abstract (arXiv)
The exponential growth in the number of scientific papers makes it increasingly difficult for researchers to keep track of all the publications relevant to their work. Consequently, the attention that can be devoted to individual papers, measured by their citation counts, is bound to decay rapidly. In this work we make a thorough study of the life-cycle of papers in different disciplines. Typically, the citation rate of a paper increases up to a few years after its publication, reaches a peak and then decreases rapidly. This decay can be described by an exponential or a power law behavior, as in ultradiffusive processes, with exponential fitting better than power law for the majority of cases. The decay is also becoming faster over the years, signaling that nowadays papers are forgotten more quickly. However, when time is counted in terms of the number of published papers, the rate of decay of citations is fairly independent of the period considered. This indicates that the attention of scholars depends on the number of published items, and not on real time.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Mar 2015.
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Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 1.
4 papers.
- 2023Forgotten Knowledge: Examining the Citational Amnesia in NLPcited by 13
- 2024Citation Amnesia: On The Recency Bias of NLP and Other Academic Fieldscited by 5
- 2026Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Userscited by 2
- 2024Is there really a Citation Age Bias in NLP?cited by 1
- 2026Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users17 Mar 2026
- 2024Citation Amnesia: On The Recency Bias of NLP and Other Academic Fields19 Feb 2024
- 2024Is there really a Citation Age Bias in NLP?7 Jan 2024
- 2023Forgotten Knowledge: Examining the Citational Amnesia in NLP29 May 2023