Countries citing papers authored by Mark A. Finlayson
Since
Specialization
Citations
This map shows the geographic impact of Mark A. Finlayson'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 Mark A. Finlayson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Finlayson more than expected).
Fields of papers citing papers by Mark A. Finlayson
This network shows the impact of papers produced by Mark A. Finlayson. 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 Mark A. Finlayson. The network helps show where Mark A. Finlayson may publish in the future.
Co-authorship network of co-authors of Mark A. Finlayson
This figure shows the co-authorship network connecting the top 25 collaborators of Mark A. Finlayson.
A scholar is included among the top collaborators of Mark A. Finlayson 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 Mark A. Finlayson. Mark A. Finlayson is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Finlayson, Mark A., et al.. (2020). Evaluating Information Loss in Temporal Dependency Trees.. Language Resources and Evaluation. 2148–2156.1 indexed citations
Gao, Tian, et al.. (2018). Identifying the Discourse Function of News Article Paragraphs. International Conference on Computational Linguistics. 25–33.15 indexed citations
8.
Finlayson, Mark A., et al.. (2018). A New Approach to Animacy Detection. International Conference on Computational Linguistics. 1–12.12 indexed citations
Dominey, Peter Ford, et al.. (2017). Dynamic Construction Grammar and Steps Towards the Narrative Construction of Meaning.. National Conference on Artificial Intelligence.6 indexed citations
11.
Finlayson, Mark A., et al.. (2014). Computational Models of Narrative: Using Artificial Intelligence to Operationalize Russian Formalist and French Structuralist Theories.. DH.1 indexed citations
12.
Finlayson, Mark A., Jeffry R. Halverson, & Steven R. Corman. (2014). The N2 corpus: A semantically annotated collection of Islamist extremist stories. Language Resources and Evaluation. 896–902.12 indexed citations
Finlayson, Mark A., Dedre Gentner, Richard J. Gerrig, et al.. (2013). Computational and Cognitive Aspects of Narrative. Cognitive Science. 35(35). 81–82.1 indexed citations
15.
Finlayson, Mark A., et al.. (2011). Detecting Multi-Word Expressions Improves Word Sense Disambiguation. Meeting of the Association for Computational Linguistics. 20–24.18 indexed citations
16.
Finlayson, Mark A.. (2010). Computational models of narrative : papers from the AAAI Fall Symposium.2 indexed citations
17.
Hervás, Raquel & Mark A. Finlayson. (2010). The Prevalence of Descriptive Referring Expressions in News and Narrative. DSpace@MIT (Massachusetts Institute of Technology). 49–54.7 indexed citations
18.
Finlayson, Mark A., Pablo Gervás, Erik T. Mueller, Srini Narayanan, & Patrick Henry Winston. (2010). Preface: Computational Models of Narrative. National Conference on Artificial Intelligence.2 indexed citations
19.
Finlayson, Mark A. & Patrick Henry Winston. (2005). Intermediate Features and Informational-level Constraint on Analogical Retrieval. eScholarship (California Digital Library). 27(27).5 indexed citations
20.
Finlayson, Mark A. & Patrick Henry Winston. (2004). A Model of Analogical Retrieval Using Intermediate Features. eScholarship (California Digital Library). 26(26).1 indexed citations
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.