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Main Conference Papers
[C16] Islam, A.A. & Finlayson, M.A. (2024) A Semantic Interpreter for Social Media Handles. In Proceedings of the 18th International AAAI Conference on Web and Social Medica (ICWSM 2024), Buffalo, NY. 679–690. doi:10.1609/icwsm.v18i1.31343 (bib, web, code)
[C15] Yarlott, W.V.H., Acharya, A., Castro Estrada, D., Gomez, D., & Finlayson, M.A. (2024) GOLEM: Gold standard for Learning and Evaluation of Motifs. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), Turin, Italy. 7801–7813. (bib, web, code)
[C14] Ocal, M., Radas, A., Hummer, J., Megerdoomian, K. & Finlayson, M.A. (2022) A Comprehensive Evaluation and Correction of the TimeBank Corpus. In Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022), Marseille, France. 2919–2927. (bib, web, code)
[C13] Ocal, M., Perez, A., Radas, A., & Finlayson, M.A. (2022) Holistic Evaluation of Automatic TimeML Annotators. In Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022), Marseille, France. 1444–1453. (bib, web, code)
[C12] Jahan, L., Mittal, R., & Finlayson, M.A. (2021) Inducing Stereotypical Character Roles from Plot Structure. In Proceedings of the 25th Conference on Empirical Methods in Natural Language Process (EMNLP 2021), Punta Cana, Dominican Republic (Online). 492–497. doi:10.18653/v1/2021.emnlp-main.39 (bib, web, code)
[C11] Jahan, L., Mittal, R., Yarlott, W.V.H. & Finlayson, M.A. (2020) A Straightforward Approach to Narratologically Grounded Character Identification. In Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), Barcelona, Spain (Online). 6089–6100. doi:10.18653/v1/2020.coling-main.536 (bib, web, code)
[C10] Aldawsari, M., Perez, A., Banisakher, D. & Finlayson, M.A. (2020) Distinguishing Between Foreground and Background Events in News. In Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), Barcelona, Spain (Online). 5171–5180. doi:10.18653/v1/2020.coling-main.453 (bib, web, code)
[C9] Ocal, M. & Finlayson, M.A. (2020) Evaluating Information Loss in Temporal Dependency Trees. In Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020), Marseille, France. 2148–2156. (bib, web, code)
[C8] Aldawsari, M. & Finlayson, M.A. (2019) Detecting Event Hierarchies using Discourse and Narrative Features. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy. 4780–4790. doi:10.18653/v1/P19-1471 (web)
[C7] Jahan, L., Chauhan, G. & Finlayson, M.A. (2018) A New Approach to Animacy Detection. In Proceedings of the 27th Conference on Computational Linguistics, (COLING 2018), Santa Fe, NM. 1–12. (code, web)
[C6] Banisakher, D., Presa Reyes, M.E., Eisenberg, J.D., Allen, J. Finlayson, M.A., Price, R., & Chen, S.-C. (2018) Ontology-Based Supervised Concept Learning for the Biogeochemical Literature. In Proceedings of the 19th IEEE International Conference on Information Reuse and Integration for Data Science (IEEE IRI 2018), Salt Lake City, UT. 402–410. doi:10.1109/iri.2018.00066 (web)
[C5] Eisenberg, J.D. & Finlayson, M.A. (2017) A Simpler and More Generalizable Story Detector
using Verb and Character Features. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017), Copenhagen, Denmark. 2708–2715. doi:10.18653/v1/D17-1287
[C4] Eisenberg, J.D., Banisakher, D., Presa, M., Unthank, K. Finlayson, M.A., Price, R., & Chen, S.-C. (2017) Toward Semantic Search for the Biogeochemical Literature. In Proceedings of the 18th IEEE International Conference on Information Reuse and Integration (IEEE IRI 2017), San Diego, CA. 517–525. doi:10.1109/iri.2017.49 (web)
[C3] Finlayson, M.A., Halverson, J.R., & Corman, S.R. (2014) The N2 Corpus: A Semantically Annotated Collection of Islamist Extremist Stories. In Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014), Reykjavik, Iceland. 896–902. (web)
[C2] Hervás, R., & Finlayson, M.A. (2010) The Prevalence of Descriptive Referring Expressions in News and Narrative. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden. 49–54. (web)
[C1] Finlayson, M.A., & Winston, P.H. (2005) Intermediate Features and Informational-level Constraint on Analogical Retrieval. In Proceedings of the 27th Annual Meeting of the Cognitive Science Society (CogSci 2005), Stresa, Italy. 666–671.
Journal Articles
[J9] Pairolero, N.A., Giczy, A.V., Torres, G., Erana, T.I., Finlayson, M.A., Toole, A.A. (2025) The artificial intelligence patent dataset (AIPD) 2023 update. Journal of Technology Transfer. Published online 22 February 2025. doi:10.1007/s10961-025-10189-8. (web)
[J8] Öztekin, I., Garic, D., Bayat, M., Hernandez, M.L., Finlayson, M.A., Graziano, P.A., Dick, A.S. (2022) Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children. European Journal of Neuroscience, 56(12) 6239–6257, article 15842. doi:10.1111/ejn.15842. (bib, web)
[J7] Öztekin, I., Finlayson, M.A., Graziano, P.A., Dick, A.S. (2021) Is there any incremental benefit to conducting neuroimaging and neurocognitive assessments in the diagnosis of ADHD in young children? A machine learning investigation. Developmental Cognitive Neuroscience, 49(11), article 100966. doi:10.1016/j.dcn.2021.100966 (bib, web)
[J6] Himmelstein P., Barb S., Finlayson M.A., Young, K.D. (2018) Linguistic Analysis of the Autobiographical Memories of Individuals with Major Depressive Disorder. PLoS ONE, 13(11), article 0207814. doi:10.1371/journal.pone.0207814 (web)
[J5] Mealier, A.-L., Pointeau, G., Mirliaz, S., Ogawa, K., Finlayson, M.A., & Dominey, P.F. (2017) Narrative Constructions for the Organization of Self Experience: Proof of Concept via Embodied Robotics. Frontiers in Psychology, 8, article 1331. doi:10.3389/fpsyg.2017.01331 (web)
[J4] Finlayson, M.A. (2016) Inferring Propp’s Functions from Semantically Annotated Text. Journal of American Folklore, 129(511) 53–75. (web)
→ Also translated into Chinese: Finlayson, M.A., Zhang, R., & Li, Y. (2019) Inferring Propp’s Functions from Semantically Annotated Text. Folklore Studies, 146(04), 117–134. doi:10.13370/j.cnki.fs.2019.04.012 (web)
[J3] Finlayson, M.A. (2015) ProppLearner: Deeply Annotating a Corpus of Russian Folktales to Enable the Machine Learning of a Russian Formalist Theory. Digital Scholarship in the Humanities (DSH), doi:10.1093/llc/fqv067 (web)
[J2] Finlayson, M.A. & Corman, Steven R. (2013) The Military Interest in Narrative. Sprache und Datenverarbeitung (Speech and Data Processing), 37(1–2) 173–191. (web)
[J1] Finlayson, M.A. (2013) A Survey of Corpora in Computational and Cognitive Narrative Science. Sprache und Datenverarbeitung (Speech and Data Processing), 37(1–2) 113–141. (data, web)
Papers in Smaller Conferences, Demonstration Sessions, Workshops, & Symposia
[W36] Islam, A.A. & Finlayson, M.A. (2025, in press) COGNAC at SemEval-2025 Task 10: Multi-level Narrative Classification with Summarization and Hierarchical Prompting. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), Vienna, Austria.
[W35] Bogosian, B., Vassigh, S., Kaur, B.K., Corrigan, S., Perez, G., Lor, M.A., Vodinepally, B., Erana, T.I., Finlayson, M.A., & Chen, S.-C. (2025) Work in Progress: VR-based Robotics Training for EC Industry. In Proceedings of the 9th IEEE World Engineering Education Conferenc (EDUNINE 2025), Montevideo, Uruguay. 1–4. doi:10.1109/EDUNINE62377.2025.10980843 (bib, web)
[W34] Brito, F., Mekdad, Y., Ross, M., Finlayson, M.A., & Uluagac, S. (2025) Enhancing Cybersecurity Education with Artificial Intelligence Content. In Proceedings of the 56th ACM Technical Symposium on Computer Science Education (SIGCSETS 2025), Pittsburgh, PA. 158–164. doi:10.1145/3641554.3701958 (bib, web)
[W33] Acharya, A., Castro Estrada, D., Yarlott, W.V.H., Gomez, D., & Finlayson, M.A. (2024) Discovering Implicit Meanings of Cultural Motifs from Text. In Proceedings of the 6th Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024), Mexico City, Mexico. 45–56. doi:10.18653/v1/2024.nlpcss-1.4 (bib, web)
[W32] Ocal, M., Singh, A., & Finlayson, M.A. (2024) Estimating Narrative Durations: Proof of Concept. In Proceedings of the 7th International Workshop on Narrative Extraction from Texts, Glasgow, Scotland. 41–52. (web)
[W31] Singh, A., Hummer, J., Ocal, M., & Finlayson, M.A. (2024) pyTLEX: A Python Library for TimeLine EXtraction. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations (EACL Demos 2024), St. Julian, Malta. 27–34. (bib, code, web)
[W30] Ocal, M., Singh, A., Hummer, J., Radas, A., & Finlayson, M.A. (2023) jTLEX: a Java Library for TimeLine EXtraction. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations (EACL Demos 2023), Dubrovnik, Croatia. 27–34. (web)
[W29] Aris, A., Rondon, L.P., Ortiz, L., Ross, M., Finlayson, M.A., & Uluagac, S. (2022) Integrating Artificial Intelligence into Cybersecurity Curriculum: New Perspectives. In Proceedings of the 2022 American Society for Engineering Education Annual Conference & Exposition (ASEE 2022), Minneapolis, MN. (web)
[W28] Yarlott, W.V.H., Ochoa, A., Acharya, A., Bobrow, L., Estrada, D.C., Gomez, D., Zheng, J., McDonald, D., Miller, C. & Finlayson, M.A. (2021) Finding Trolls Under Bridges: Preliminary Work on a Motif Detector. In Proceedings of the 9th Annual Conference on Advances in Cognitive Systems (ACS 2021), Online. Paper 23. (arXiv, web)
[W27] Zad, S., Jimenez, J. & Finlayson, M.A. (2021) Hell Hath No Fury? Correcting Bias in the NRC Emotion Lexicon. In Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH), Online. 102–113. doi:10.18653/v1/2021.woah-1.11 (bib, web, code)
[W26] Acharya, A., Talamadupula, K. & Finlayson, M.A. (2021) Toward an Atlas of Cultural Commonsense for Machine Reasoning. In Proceedings of the Workshop on Common Sense Knowledge Graphs (CSKGs), Online. (bib, web)
[W25] Aldawsari, M., Asgari, E. & Finlayson, M.A. (2020) Story Fragment Stitching: The Case of the Story of Moses. In Proceedings of the 1st Workshop on Artificial Intelligence for Narratives (AI4N 2020), Yokohama, Japan (Online). 47–54. (bib, web, code)
[W24] Jahan, L., Yarlott, W.V.H., Mittal, R. & Finlayson, M.A. (2020) Confirming the Generalizability of a Chain-Based Animacy Detector. In Proceedings of the 1st Workshop on Artificial Intelligence for Narratives (AI4N 2020), Yokohama, Japan (Online). 43–46. (bib, code, web)
[W23] Zad, S. & Finlayson, M.A. (2020) Systematic Evaluation of a Framework for Unsupervised Emotion Recognition for Narrative Text. In Proceedings of the 1st Joint Workshop on Narrative Understanding, Storylines, and Events (NUSE 2020), Online. 26–37. doi:10.18653/v1/2020.nuse-1.4 (web, code)
[W22] Banisakher, D., Yarlott, W.V., Aldawsari, M., Rishe, N. & Finlayson, M.A. (2020) Improving the Identification of the Discourse Function of News Article Paragraphs. In Proceedings of the 1st Joint Workshop on Narrative Understanding, Storylines, and Events (NUSE 2020), Online. 17–25. doi:10.18653/v1/2020.nuse-1.3 (web)
[W21] Cremisini, A. & Finlayson, M.A. (2020) New Insights into Cross-Document Event Coreference: Systematic Comparison and a Simplified Approach. In Proceedings of the 1st Joint Workshop on Narrative Understanding, Storylines, and Events (NUSE 2020), Online. 1–10. doi:10.18653/v1/2020.nuse-1.1 (web, code)
[W20] Jahan, L. & Finlayson, M.A. (2019) Character Identification Refined: A Proposal. In Proceedings of the 1st Workshop on Narrative Understanding (WNU), Minneapolis, MN. 12–18. doi:10.18653/v1/W19-2402 (web)
[W19] Cremisini, A., Aguilar, D., & Finlayson, M.A. (2019) A Challenging Dataset for Bias Detection: The Case of the Crisis in the Ukraine. In Proceedings of the 2019 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS), Washington DC. 173–183. doi:10.1007/978-3-030-21741-9_18. (web)
[W18] Banisakher, D., Rishe, N. & Finlayson, M.A. (2018) Automatically Detecting the Position and Type of Psychiatric Evaluation
Report Sections. In Proceedings of the 9th International Workshop on Health Text Mining and Information Analysis (LOUHI 2018), Brussels, Belgium. 101–110. doi:10.18653/v1/W18-5612 (web)
[W17] Yarlott, W.V.H., Cornelio, C., Gao, T. & Finlayson, M.A. (2018) Identifying the Discourse Function of News Article Paragraphs. In Proceedings of the Workshop on Events and Stories in the News (EventStory 2018), Santa Fe, NM. 25–33. (web)
[W16] Zevenbergen, B., Finlayson, M.A., Kortz, M., Pagallo, U., Schaich Borg, J., & Zapušek, T. (2018) Appropriateness and Feasibility of Legal Personhood for AI Systems. In Proceedings of the 3rd International Conference on Robot Ethics and Standards (ICRES 2018), Troy, NY. 59–64. doi:10.13180/icres.2018.20-21.08.017 (web)
[W15] Jahan, L., Chauhan, G. & Finlayson, M.A. (2017) Building on Word Animacy to Determine Coreference Chain Animacy in Cultural Narratives. In Proceedings of the 10th Workshop on Intelligent Narrative Technologies (INT10), Salt Lake City, UT. 198–203. doi:10.1609/aiide.v13i2.12993 (web)
[W14] Dominey, P.F., Mealier, A.-L., Pointeau, G., Mirliaz, S. & Finlayson, M.A. (2017) Dynamic Construction Grammar and Steps Towards the Narrative Construction of Meaning. In Proceedings of the AAAI 2017 Spring Symposium on Computational Construction Grammar and Natural Language Understanding, Stanford, CA. 163–170. (web)
[W13] Eisenberg, J.D. & Finlayson, M.A. (2016) Automatic Identification of Narrative Diegesis and Point of View. In Proceedings of the 2nd Workshop on Computing News Storylines (CNS 2016), Austin, TX. 36–46. doi:10.18653/v1/W16-5705 (web, code)
[W12] Yarlott, W.V.H. & Finlayson, M.A. (2016) ProppML: A Complete Annotation Scheme for Proppian Morphologies. In Proceedings of the 7th International Workshop on Computational Models of Narrative (CMN'16), Krakow, Poland. Paper 8. doi:10.4230/OASIcs.CMN.2016.8 (web)
[W11] Yarlott, W.V.H. & Finlayson, M.A. (2016) Learning a Better Motif Index: Toward Automated Motif Extraction. In Proceedings of the 7th International Workshop on Computational Models of Narrative (CMN'16), Krakow, Poland. Paper 7. doi:10.4230/OASIcs.CMN.2016.7 (web)
[W10] Eisenberg, J.D., Yarlott, W.V.H., & Finlayson, M.A. (2016) Comparing Extant Story Classifiers: Results & New Directions. In Proceedings of the 7th International Workshop on Computational Models of Narrative (CMN'16), Krakow, Poland. Paper 6. doi:10.4230/OASIcs.CMN.2016.6 (web)
[W9] Finlayson, M.A. (2014) Java Libraries for Accessing the Princeton Wordnet: Comparison and Evaluation. In Proceedings of the 7th International Global WordNet Conference (GWC 2014), Tartu, Estonia. 78–85. (web) Tool download [P5].
[W8] Asgari, E., Ghassemi, M., & Finlayson, M.A. (2013) Confirming the themes and interpretive unity of Ghazal poetry using topic models. In Proceedings of the NIPS Workshop on Topic Models: Computation, Application, and Evaluation, Lake Tahoe, NV. Submission 18.
[W7] Finlayson, M.A. (2011) The Story Workbench: An Extensible Semi-Automatic Text Annotation Tool. In Proceedings of the 4th Workshop on Intelligent Narrative Technologies (INT4), Stanford, CA. 21–24. doi:10.1609/aiide.v7i2.12458 (web, tool→[S4]).
[W6] Finlayson, M.A. (2011) Corpus Annotation in Service of Intelligent Narrative Technologies. In Proceedings of the 4th Workshop on Intelligent Narrative Technologies (INT4), Stanford, CA. 17–20. doi:10.1609/aiide.v7i2.12459 (web)
[W5] Kulkarni, N., & Finlayson, M.A. (2011) jMWE: A Java Toolkit for Detecting Multi-Word Expressions. In Proceedings of the 8th Workshop on Multiword Expressions: from Parsing and Generation to the Real World (MWE 2011), Portland, OR. 122–124. (web, code)
[W4] Finlayson, M.A., & Kulkarni, N. (2011) Detecting Multi-Word Expressions improves Word Sense Disambiguation. In Proceedings of the 8th Workshop on Multiword Expressions: from Parsing and Generation to the Real World (MWE 2011), Portland, OR. 20–24. (web, code)
[W3] Finlayson, M.A. (2010) Learning Narrative Morphologies from Annotated Folktales. In Proceedings of the 1st Automated Motif Discovery in Cultural Heritage and Scientific Communication Texts Workshop (AMICUS), Vienna, Austria. 99–102.
[W2] Finlayson, M.A. (2009) Deriving Narrative Morphologies via Analogical Story Merging. In Proceedings of the 2nd International Conference on Analogy (published as “New Frontiers in Analogy Research”, New Bulgarian University Press), Sofia, Bulgaria. 127–136.
[W1] Finlayson, M.A. (2008) Collecting Semantics in the Wild: The Story Workbench. In Proceedings of the AAAI Fall Symposium on Naturally Inspired Artificial Intelligence (Published as Technical Report FS-08-06, Papers from the AAAI Fall Symposium, AAAI Press, Menlo Park, CA), Arlington, VA. 46–53. (web)
Book Chapters & Invited Articles
[B4] Finlayson, M.A., Cremisini, A., & Ocal, M. (2022) Extracting and Aligning Timelines. In Computational Analysis of Storylines: Making Sense of Events, edited by T. Caselli, E. Hovey, M. Palmer, & P. Vossen. Cambridge University Press: Cambridge. 87–105. doi:10.1017/9781108854221.006 (web)
[B3] Eisenberg, J.D. & Finlayson, M.A. (2019) Narrative Boundaries Annotation Guide. In the Special Issue "A Shared Task for the Digital Humanities: Annotating Narrative Levels" of the Journal of Cultural Analytics, edited by E. Gius, N. Reiter, & M. Willand, Article No. 11199. doi:10.22148/16.051 (web)
[B2] Finlayson, M.A. & Erjavec, T. (2016) Overview of Annotation Creation: Processes & Tools. In Handbook of Linguistic Annotation, edited by N. Ide and J. Pustejovsky. Springer: Dordrecht. 167–191. doi:10.1007/978-94-024-0881-2_5 (web)
[B1] Finlayson, M.A. (2012) Sets of Signals, Information Flow, and Folktales. In Proceedings of the Turing Centenary Conference and 8th Conference on Computability in Europe (CiE 2012), Cambridge, UK (Published as "How the World Computes", Lecture Notes in Computer Science [LNCS] No. 7318, Springer: Berlin / Heidelberg). 228–236. doi:10.1007/978-3-642-30870-3_23 (web)
Technical Reports
[R8] Erana, T.I. & Finlayson, M.A. (2024) Automated Neural Patent Landscaping in the Small Data Regime. Florida International University: Miami, FL. doi:10.48550/arXiv.2407.08001. (web)
[R7] Ocal, M., Xie, N., & Finlayson, M.A. (2024) TLEX: An Efficient Method for Extracting Exact Timelines from TimeML Temporal Graphs. Florida International University: Miami, FL. doi:10.48550/arXiv.2406.05265. (web)
[R6] Gocso, A., Perez Brito, C., Ruesca, B., Mendes, A., Finlayson, M.A. (2023) Using the SP!CE Framework to Code Influence Campaign Activity on Social Media: Case Study on the 2022 Brazilian Presidential Election. Florida International University: Miami, FL. arXiv 2312.02810. doi:10.48550/arXiv.2406.05265. (data, web)
[R5] Venhaus, M., Fulk, M., Finlayson, M.A., Fonseca, B., Lopez Diaz, Z., Sixto, D., Koda, S. (2021) Structured Process for Information Campaign Evaluation (SP!CE): An Analytic Framework, Knowledge Base, and Scoring Rubric for Operations in the Information Environment. The MITRE Corporation: Anapolis, MD. Product MP210039.
[R4] Finlayson, M.A. (2016) Report on the 2015 NSF Workshop on Unified Annotation Tooling. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL): Cambridge, MA. Technical Report No. MIT-CSAIL-TR-2016-014. hdl:1721.1/105270 (web)
[R3] Finlayson, M.A., & Hervás, R. (2010) Annotation Guide for the UCM/MIT Indications, Referential Expressions, and Coreference Corpus (UMIREC Corpus). MIT Computer Science and Artificial Intelligence Laboratory (CSAIL): Cambridge, MA. Technical Report No. MIT-CSAIL-TR-2010-025. hdl:1721.1/54765 (web)
[R2] Richards, W., Finlayson, M.A., & Winston, P.H. (2009) Advancing Computational Models of Narrative. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL): Cambridge, MA. Technical Report No. MIT-CSAIL-TR-2009-063. hdl:1721.1/50232 (web)
[R1] Finlayson, M.A., & Winston, P.H. (2006) Analogical Retrieval via Intermediate Features: The Goldilocks Hypothesis. MIT Computer Science and Artificial Intelligence Laboratory (CSAIL): Cambridge, MA. Technical Report No. MIT-CSAIL-TR-2006-071. hdl:1721.1/34635 (web)
Book Reviews
[V1] Finlayson, M.A. (2013) Book Review: Computational Modeling of Narrative, by Inderjeet Mani. Natural Language Engineering, 20(2), 289–292. doi:10.1017/S135132491300017X (web)
Software & Corpora
[S8] Singh, A., Hummer, J., Ocal, M., & Finlayson, M.A. (2024) pyTLEX: A Python Library for TimeLine EXtraction. Described in [W31]
[S8] Ocal, M., Singh, A., Radas, A., Hummer, J., & Finlayson, M.A. (2023) jTLEX: A Java Library for TimeLine EXtraction. Described in [W30]
[S7] Finlayson, M.A., Halverson, J.R., & Corman, S.R. (2014) The Narrative Networks Corpus: A Semantically Annotated Collection of Islamist Extremist Stories (N2 Corpus). MIT CSAIL Work Product. hdl:1721.1/57507. Described in [C3]
[S6] Finlayson, M.A. (2013) jVerbnet: A Java Library for Interfacing with Verbnet.
[S5] Finlayson, M.A. (2013) JWI: The MIT Java Interface to Wordnet. Described in [W9].
[S4] Finlayson, M.A. (2013) The Story Workbench: A General Purpose Text Annotation Tool. Described in [W1,W6].
[S3] Finlayson, M.A. (2011). jSemcor: A Java Library for Interfacing with Semcor.
[S2] Finlayson, M.A., & Kulkarni, N. (2011) jMWE: A Java Library for Detecting Multi-Word Expressions. Described in [W4,W5].
[S1] Finlayson, M.A. & Hervás, R. (2010) UCM/MIT Indications, Referring Expressions, and Co-Reference Corpus (UMIREC corpus). MIT CSAIL Work Product. hdl:1721.1/57507. Described in [C2], annotation Guide at [R3].
Other Works
[O8]
Azizinamini, A. & Finlayson, M.A. (2025) Artificial Intelligence Methods Can Assist Bridge Engineers. ASPIRE: The Concrete Bridge Magazinee. 19(2), 8–9. (web)
[O7]
Forbus, K. & Finlayson, M.A. (2020) Patrick Henry Winston – Two Reflections. AI Magazine. 41(1), 106–108. doi:10.1609/aimag.v41i1.5303 (web)
[O6]
Jahan, L., Chauhan, G., & Finlayson, M.A. (2018) Building on Word Animacy to Determine Coreference Chain Animacy in Cultural Narratives. Proceedings of the 2nd Workshop on Widening NLP (WiNLP 2018). Paper 7. Condensed version of [W15]
[O5]
Finlayson, M.A. (2012) Learning Narrative Structure from Annotated Folktales. Doctoral Dissertation. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. hdl:1721.1/71284 (web)
[O4]
Finlayson, M.A. (2011) Reports of the AAAI 2010 Fall Symposia: Computational Models of Narrative. AI Magazine. 32(1), 96–97. doi:10.1609/aimag.v32i1.2338 (web)
[O3]
Finlayson, M.A., Richards W., & Winston, P.H. (2010) Computational Models of Narrative: Review of the Workshop. AI Magazine, 31(2), 97–100. doi:10.1609/aimag.v31i2.2295 (web)
[O2]
Finlayson, M.A. (2001) Development of a Scintillating Reference Grid for Spatial-Phase-Locked Electron-Beam Lithography. Master of Science Dissertation. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. hdl:1721.1/16793 (web)
[O1]
Hastings, J.T., Zhang, F., Finlayson, M.A., Goodberlet, J.G., & Smith, H.I. (2000) Two-dimensional spatial-phase-locked electron-beam lithography via sparse sampling. Journal of Vaccum Science and Technology B, 18(6), 3268–3271. doi:10.1116/1.1314371 (web)
Citable Abstracts & Posters
[A17]
Corrigan, S., Vassigh, S., Kaur, B., Finlayson, M.A., Erana, T.I., Perez, G., Vodinepally, B., Bogosian, B., Lor, M.A., & Chen, S.-C. (2025, in press) The architecture and early results of the IL-PRO AI-driven immersive and adaptive learning system for industrial robotics, Proceedings of the International Applied Human Factors and Ergonomics Conference (AHFE 2025), Orlando, FL.
[A16]
Lor, M.A., Vodinepally, B., Erana, T.I., Kaur, B., Perez, G., Corrigan, S., Chen, S.-C., Finlayson, M.A., Bogosian, B., & Vassigh, S. (2025, in press) An AI-based adaptive pipeline for automated feedback in immersive robotics learning, in Proceedings of the International Applied Human Factors and Ergonomics Conference (AHFE 2025), Orlando, FL.
[A15]
Öcal, M. & Finlayson, M.A. (2025) Enhancing Medical Narrative Analysis with TLEX, presented at the 2025 Baptist Health Academic Conference, Miami, FL.
[A14]
Finlayson, M.A. (2022) Next Steps in Modeling Social Media: The Importance of Narrative, Proceedings of the 7th International Workshop on Social Sensing (SocialSens 2022), Special Edition on Information Operations and Belief Dynamics on Social Media, held in conjunction with the 16th International Conference on Web and Social Media (ICWSM 2022), Atlanta, GA. doi:10.36190/2022.23 (web)
[A13]
Srivastava, K., Moreo, A., Beldona, S., Traynor, M., Finlayson, M.A., & Alonso Jr., M. (2020) A Pilot Investigation into Measuring the Gap between Restaurant Industry Interests and Academic Research using Natural Language Processing, Proceedings of the 5th Annual International Council on Hotel, Restaurant, and Institutional Education–Southeast, Central & South American Federation Conference (ICHRIE-SECSA 2020), Auburn, AL. 147–148.
[A12]
Ochoa, A.J. & Finlayson, M.A. (2019) POSTER: Analysis and Parsing of Unstructured Cyber-Security Incident Data, Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks (WiSec'19), Miami, FL. 1345–1346. doi:10.1145/3317549.3326324 (web)
[A11]
Baniskher, D. & Finlayson, M.A. (2016) A Supervised Classification Approach to Predicting Knee Pain Improvement in Osteoarthritis Patients, Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2017), Marco Island, FL. 774. Best Poster Award. (web)
[A10]
Eisenberg, J. & Finlayson, M.A. (2016) Comparison of Story Classification Methods across New Annotated Data, Linguistics Matters (FLYM 2016), Miami, FL. 45–46
[A9]
Sack, G.A., Finlayson, M.A., Gervás, P. (2014) Computational Models of Narrative: Using Artificial Intelligence to Operationalize Russian Formalist and French Structuralist Theories, Digital Humanities 2014 (DH), Lausanne, Switzerland.
[A8]
Finlayson, M.A. & Winston, P.H. (2011) Narrative is a Key Cognitive Competency, in Proceedings of the 2nd Annual International Conference on Biologically Inspired Cognitive Architectures (BICA 2011), Arlington, VA. 110. (Published as Volume 233 in Frontiers in Artificial Intelligence and Applications, IOS Press, Clifton, VA) (web)
[A7]
Kraemer, J., Finlayson, M.A., Ichinco, D. & Gibson, E. (2008) Advances in Discourse: Theory and Annotation, in Proceedings of the Conference on Processing Text-Technological Resources (PTTR), Bielefeld, Germany.
[A6]
Finlayson, M.A. & Winston, P.H. (2007) Reasoning by Imagining: The Neo-Bridge System, in the MIT CSAIL Research Abstracts for 2007. (web)
[A5]
Finlayson, M.A. & Winston, P.H. (2007) The Rapid Story Annotation Workbench, in the MIT CSAIL Research Abstracts for 2007. (web)
[A4]
Finlayson, M.A. & Winston, P.H. (2005) Computational Principles of Human Analogical Reasoning, in the MIT CSAIL Research Abstracts for 2005. (web)
[A3]
Finlayson, M.A. & Winston, P.H. (2005) Intermediate Features Improve Incremental Analogical Mapping, in Proceedings of the 27th Annual Meeting of the Cognitive Science Society (CogSci 2005), Stresa, Italy. 2477.
[A2]
Winston, P.H. & Finlayson, M.A. (2004) Computational Politics, in the MIT CSAIL Research Abstracts for 2004. 783–784. (web)
[A1]
Finlayson, M.A. & Winston, P.H. (2004) A Model of Analogical Retrieval using Intermediate Features, in Proceedings of the 26th Annual Meeting of the Cognitive Science Society (CogSci 2004), Chicago, IL. 1557. (web)
Edited Collections & Meetings Organized
[E12] Campos, R., Alí, M.J., Jatowt, A., Bhatia, S. & Finlayson, M.A. (Editors) (2021) Proceedings of the 4th International Workshop on Narrative Extraction from Texts (Text2Story 2021), Online. Co-located with the 43rd European Conference on Information Retrieval (ECIR 2021). Published as CEUR Workshop Proceedings [CEUR-WS] Vol. 2860. (website)
[E11] Finlayson, M.A., Miller, B., Lieto, A., & Ronfard, R. (Editors) (2016) Proceedings of the 7th Workshop on Computational Models of Narrative (CMN’16), Krakow, Poland. Co-located with Digital Humanities 2016. Published as Open Access Series in Informatics [OASIcs] Vol. 53. Saarbrücken/Wadern, Germany: Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. doi:10.4230/OASIcs.CMN.2016.0. (website)
[E10]
Caselli, T., Erp, M.v., Minard, A.-L., Finlayson, M.A., Miller, B., Aterias, J., Balahur, A., Vossen, P. (Editors) (2015) Proceedings of the First Workshop on Computing News Storylines (CNewsStory 2015). Beijing, China. doi:10.18653/v1/W15-45
[E9] Finlayson, M.A. (Organizer) (2015) The NSF-Sponsored Workshop on Unified Annotation Tooling. Described in [R4].
[E8] Finlayson, M.A., Miller, B., Lieto, A., & Ronfard, R. (Editors) (2015) Proceedings of the 6th Workshop on Computational Models of Narrative (CMN’15), Atlanta, GA. Co-located with the 3rd Annual Conference on Advances in Cognitive Systems. Published as Open Access Series in Informatics [OASIcs] Vol. 45. Saarbrücken/Wadern, Germany: Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. doi:10.4230/OASIcs.CMN.2015.i. (website)
[E7]
Finlayson, M.A., Gervás, P., Yuret, D., & Bex, F. (Guest Editors) (2014) Special Issue 'Computational Models of Narrative' LLC. The Journal of Digital Scholarship in the Humanities. 29(4). doi:10.1093/llc/fqu053
[E6] Finlayson, M.A., Meister, J.C., & Bruneau, E.G. (Editors) (2014) Proceedings of the 5th Workshop on Computational Models of Narrative (CMN’14), Quebec City, Canada. Published as Open Access Series in Informatics [OASIcs] Vol. 41. Saarbrücken/Wadern, Germany: Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. doi:10.4230/OASIcs.CMN.2014.i. (website)
[E5] Finlayson, M.A., Fisseni, B., Löwe, B., & Meister, J.C. (Editors) (2013) Proceedings of the 4th Workshop on Computational Models of Narrative (CMN’13), Hamburg, Germany. Held as a satellite workshop of the 35th Meeting of the Cognitive Science Society (CogSci 2013). Published as Open Access Series in Informatics [OASIcs] Vol. 32. Saarbrücken/Wadern, Germany: Schloss Dagstuhl – Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing. doi:10.4230/OASIcs.CMN.2013.i (website)
[E4]
Finlayson, M.A., (Organizer) Fisseni, B., Genter, D., Gerrig, R., Löwe, B., Loewenstein, J., Mani, I., Meister, J.C., & Young, R.M. (Speakers) (2013) Symposium on Computational and Cognitive Aspects of Narratives. In Proceedings of the 35th Meeting of the Cognitive Science Society (CogSci 2013). Berlin, Germany. 81–82. (web)
[E3] Finlayson, M.A., Gervás, P., Yuret, D., & Bex, F.(Editors) (2012) Proceedings of the 3rd Workshop on Computational Models of Narrative (CMN’12), Istanbul, Turkey. As part of the Workshops of the 8th Language Resources and Evaluation Conference (LREC 2012). (website)
[E2] Finlayson, M.A., Gervás, P., Mueller, E., Narayanan, S., & Winston, P.H. (Editors) (2010) Proceedings of the 2nd Computational Models of Narrative (CMN’10), Arlington, VA. Published as Technical Report FS-10-04, papers from the Fall Symposium. Menlo Park, CA: AAAI Press. Additionally described in [O4]. (website)
[E1] Finlayson, M.A., Richards, W., & Winston, P.H. (Organizers) (2010) Workshop on Computational Models of Narrative. Beverly, MA. Described in [O3]. (no website)
Patents
[P7] Ocal, M. & Finlayson, M.A. (2025) Systems and methods for performing temporal analysis, United States Patent No. 12,293,152. May 6, Application No. 18/882,352.
[P6] Banisakher, D., Rishe, N.D. & Finlayson, M.A. (2022) Systems and methods for predicting pain level, United States Patent No. 11,537,888. December 12, Application No. 16/875,041.
[P5] Banisakher, D., Rishe, N.D. & Finlayson, M.A. (2022) Systems and methods for determining document section types, United States Patent No. 11,494,418. November 8, Application No. 17/160,712.
[P4] Ocal, M., & Finlayson, M.A. (2021) Systems and methods for evaluating temporal dependency trees, United States Patent No. 11,170,303. November 9, Application No. 17/160,606.
[P3] Banisakher, J.D., Rishe, N.D. & Finlayson, M.A. (2021) Systems and methods for segmenting documents, United States Patent No. 10,949,622. March 16, Application No. 16/667,991.
[P2] Eisenberg, J.D. & Finlayson, M.A. (2021) Features for classification of stories, United States Patent No. 10,909,324. February 2, Application No. 16/260,389.
[P1] Eisenberg, J.D. & Finlayson, M.A. (2019) Features for automatic classification of narrative point of view and diegesis, United States Patent No. 10,191,975. January 29, Application No. 15/804,589.
