Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Defining and identifying communities in networks
20041.6k citationsFederico Cecconi, Domenico Parisi et al.profile →
Countries citing papers authored by Domenico Parisi
Since
Specialization
Citations
This map shows the geographic impact of Domenico Parisi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Domenico Parisi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Domenico Parisi more than expected).
This network shows the impact of papers produced by Domenico Parisi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Domenico Parisi. The network helps show where Domenico Parisi may publish in the future.
Co-authorship network of co-authors of Domenico Parisi
This figure shows the co-authorship network connecting the top 25 collaborators of Domenico Parisi.
A scholar is included among the top collaborators of Domenico Parisi based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Domenico Parisi. Domenico Parisi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Cecconi, Federico & Domenico Parisi. (2007). Asymmetric pricing: an agent based model. international conference on Modelling and simulation. 380–385.2 indexed citations
6.
Parisi, Domenico & Marco Mirolli. (2007). Steps Towards Artificial Consciousness: A Robot's Knowledge of Its Own Body.. National Conference on Artificial Intelligence. 118–123.3 indexed citations
7.
Nolfi, Stefano, Raffaele Calabretta, John Hallam, et al.. (2006). From Animals to Animats 9: 9th International Conference on Simulation of Adaptive Behavior, SAB 2006, Rome, Italy, September 25-29, 2006, Proceedings (Lecture Notes in Computer Science). Springer eBooks.3 indexed citations
Ferdinando, Andrea Di, Anna M. Borghi, & Domenico Parisi. (2002). The Role of Action in Object Categorization. The Florida AI Research Society. 138–142.1 indexed citations
11.
Parisi, Domenico, et al.. (2002). Verbs, nouns, and simulated language games. Research Explorer (The University of Manchester). 14(1). 99–114.5 indexed citations
12.
Parisi, Domenico, Steven Michael Grice, Michael Taquino, & Duane A. Gill. (2002). Social Capital, Structural Conditions, and Mortality: A Study of Nonmetropolitan Counties in Mississippi *. Journal of Rural Social Sciences. 18(2). 5.2 indexed citations
13.
Parisi, Domenico, et al.. (2002). TANF/Welfare Client Decline and Community Context in the Rural South, 1997-2000. Journal of Rural Social Sciences. 18(1). 6.4 indexed citations
14.
Cangelosi, Angelo & Domenico Parisi. (2001). How Nouns and Verbs Differentially Affect the Behavior of Artificial Organisms. CogPrints (University of Southampton). 23(23).15 indexed citations
Parisi, Domenico. (1987). Il peso della storia. il Mulino. 555–562.1 indexed citations
19.
Parisi, Domenico, et al.. (1979). LANGUAGE AND SOCIAL ENVIRONMENT AT 2 YEARS. Merrill-palmer Quarterly. 25(1). 61–76.6 indexed citations
20.
Parisi, Domenico. (1977). Sviluppo del linguaggio e ambiente sociale.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.