PATENTS
2. Louwerse, M.M. (2014). System and method for dynamically applying line breaks in text. U.S. Patent No. 20,120,053,928. Washington, DC: U.S. Patent and Trademark Office.
1. Louwerse (2017). System and method for evaluating reading fluency using underlining. U.S. Patent No. 20,140,065,581. Washington, DC: U.S. Patent and Trademark Office.
PUBLICATIONS
Books and journals (authored, translated)
3. Louwerse, M.M. (2021). Keeping those words in mind. How language creates meaning. Washington DC, Rowman & Littlefield.
2. Louwerse, M.M. & Van Peer, W. (Eds.) (2002). Thematics: Interdisciplinary studies. Amsterdam: Benjamins.
1. Propp, V. (1997). De morfologie van het toversprookje. Vormleer van een genre [The Morphology of the Folktale. Formal Study of a Genre; transl. M. M. Louwerse]. Utrecht: Het Spectrum.
Journal publications
73. Linders, G. M., & Louwerse, M. M. (2023). Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis. Behavior Research Methods.
72. Mousavi, S.M.A., Powell, W.A., Louwerse, M.M., Hendrickson, A.T. (2023). Behavior and self-efficacy modulate learning in virtual reality simulations for training: A structural equation modeling approach. Frontiers in Virtual Reality. https://doi.org/10.3389/frvir.2023.1250823.
71. Linders, G. M., & Louwerse, M. M. (2023). Surface and contextual linguistic cues in dialog act classification: A cognitive science view. Cognitive Science, 47(10), e13367.
70. Tinga, A. M., Menger, N. S., de Back, T. T., & Louwerse, M. M. (2023). Age Differences in Learning-Related Neurophysiological Changes. Journal of Psychophysiology, 1-14.
69. Vaitonytė, J., Alimardani, M., & Louwerse, M. M. (2022). Scoping review of the neural evidence on the uncanny valley. Computers in Human Behavior Reports, 100263.
68. Vaitonytė, J., Alimardani, M., & Louwerse, M. M. (2022). Corneal reflections and skin contrast yield better memory of human and virtual faces. Cognitive Research: Principles and Implications, 7, 1-15.
67. van Weelden, E., Alimardani, M., Wiltshire, T. J., & Louwerse, M. M. (2022). Aviation and neurophysiology: A systematic review. Applied Ergonomics, 105, 103838.
66. Dai, L., Jung, M. M., Postma, M., & Louwerse, M. M. (2022). A systematic review of pedagogical agent research: Similarities, differences and unexplored aspects. Computers & Education, 104607.
65. Linders, G. M., & Louwerse, M. M. (2022). Zipf’s law revisited: Spoken dialog, linguistic units, parameters, and the principle of least effort. Psychonomic Bulletin & Review, 1-25.
64. Louwerse, M. M. (2022). Mapping out the road from corpus linguistics to psycholinguistics. Revista Signos. Estudios de Lingüística, 54(107).
63. De Back, T. T., Tinga, A. M., & Louwerse, M. M. (2021). Learning in immersed collaborative virtual environments: Design and implementation. Interactive Learning Environments, 1–19.
62. de Back, T. T., Tinga, A. M., & Louwerse, M. M. (2021). CAVE-based immersive learning in undergraduate courses: examining the effect of group size and time of application. International Journal of Educational Technology in Higher Education, 18(1).
61. Vaitonyte, J., Blomsma, P., Alimardani, M., & Louwerse, M.M. (2021). Realism of the face lies in skin and eyes: Evidence from virtual and human agents. Computers in Human Behavior Reports, 3, 100065.
60. Tinga, A.M., Clim, M., de Back, T.T., & Louwerse, M.M. (2021). Measures of prefrontal functional near-infrared spectroscopy in visuomotor learning. Experimental Brain Research, 239, 1061-1072.
59. van Limpt-Broers, H. A. T., Postma, M., & Louwerse, M. M. (2020). Creating ambassadors of planet Earth: The Overview Effect in K12 education. Frontiers in Psychology, 11.
58. de Back, T. T., Tinga, A. M., Nguyen, P., & Louwerse, M. M. (2020). Benefits of immersive collaborative learning in CAVE-based virtual reality. International Journal of Educational Technology in Higher Education.
57. Louwerse, M. M., Postma, M., Van Limpt-Broers, A., de Back, T. T., Tinga, A. M., & Horden, M. (2020). Beyond the frontiers of education: How immersive media changes the way we learn. ITU Journal: ICT Discoveries, 3(1).
56. Tinga, A. M., de Back, T. T., & Louwerse, M. M. (2020). Neurophysiological changes in visuomotor sequence learning provide insight in general learning processes: Measures of brain activity, skin conductance, heart rate and respiration. International Journal of Psychophysiology, 151, 40-48. doi:10.1016/j.ijpsycho.2020.02.015
55. He, D., He, X., Zhao, T., Wang, J., Li, L., & Louwerse, M. (2020). Does number perception cause automatic shifts of spatial attention? A study of the Att-SNARC effect in numbers and Chinese months. Frontiers in Psychology, 11, 680.
54. Tinga, A. M., de Back, T. T., & Louwerse, M. M. (2020). Non-invasive neurophysiology in learning and training: Mechanisms and a SWOT analysis. Frontiers in Neuroscience, 14, 589. doi:10.3389/fnins.2020.00589
53. Tinga, A. M., de Back, T. T., & Louwerse, M. M. (2019). Non-invasive neurophysiological measures of learning: A meta-analysis. Neuroscience & Biobehavioral Reviews.
52. Tinga, A.M., Nyklíček, I., Jansen, M.P., de Back, T., Louwerse, M.M. (2018). Respiratory biofeedback does not facilitate lowering arousal in meditation through virtual reality. Applied Psychophysiology and Biofeedback.
51. Louwerse, M.M. (2018). Knowing the meaning of a word by the linguistic and perceptual company it keeps. Topics in Cognitive Science, 10, 573–589.
50. Tillman, R. & Louwerse, M. (2018). Estimating emotions through language statistics and embodied cognition. Journal of Psycholinguistic Research, 47, 159-167.
49. Abney, D. H., Dale, R., Louwerse, M. M., & Kello, C. T. (2018). The bursts and lulls of multimodal interaction: Temporal distributions of behavior reveal differences between verbal and nonverbal communication. Cognitive Science, 143, 1297-1316.
48. Hutchinson, S. Louwerse, M.M. & (2018). Extracting social networks from language statistics. Discourse Processes, 55, 607-618.
47. Louwerse, M.M. & He, X. (2017). 语言加工中的符号相互依存：语言统计和知觉模拟的交互作用 (Symbol interdependency in language processing: Interactions between language statistics and perceptual simulation). Journal of South China Normal University, 2, 51-60.
46. Louwerse, M., & Qu, Z. (2016). Estimating valence from the sound of a word: Computational, experimental, and cross-linguistic evidence. Psychonomic Bulletin & Review, 1-7.
45. Recchia, G. & Louwerse, M.M. (2016). Archaeology through computational linguistics: Inscription statistics predict excavation sites of Indus Valley artifacts. Cognitive Science, 40, 2065-2080.
44. Price, K.W., Meisinger, E.B., Louwerse, M.M. & D’Mello, S. (2015): The contributions of oral and silent reading fluency to reading comprehension. Reading Psychology, 37, 167-201.
43. Louwerse, M. M., Hutchinson, S., Tillman, R., & Recchia, G. (2015). Effect size matters: the role of language statistics and perceptual simulation in conceptual processing. Language, Cognition and Neuroscience, 30, 4, 430-447.
42. Recchia, G., & Louwerse, M. M. (2014). Reproducing affective norms with lexical co-occurrence statistics: Predicting valence, arousal, and dominance. Quarterly Journal of Experimental Psychology, 68 (8), 1584-1598.
41. Datla, V., Lin, K. & Louwerse, M. (2014). Linguistic features predict the truthfulness of short political statements. International Journal of Computational Linguistics and Applications, 79-94.
40. Hutchinson, S., & Louwerse, M. M. (2014). Language statistics explain the spatial-numerical association of response codes. Psychonomic Bulletin and Review, 21, 470-478.
39. Hutchinson, S., & Louwerse, M. M. (2013). Statistical linguistic context and embodiment predict metaphor processing but participant gender determines how much. Cognitive Linguistics, 24, 667–687.
38. Tillman, R., Langston, W., Louwerse, M. (2013). Attribution of responsibility by Spanish and English speakers: How native Language affects our social judgments. Revista Signos, 46, 408-422.
37. Louwerse, M.M. & Hutchinson, S. (2012). Neurological evidence linguistic processes precede perceptual simulation in conceptual processing. Frontiers in Psychology, 16, 385. doi: 10.3389/fpsyg.2012.00385.
36. Louwerse, M. M. & Benesh, N. (2012). Representing spatial structure through maps and language: Lord of the Rings encodes the spatial structure of Middle Earth. Cognitive Science, 36, 1556-69.
35. Louwerse, M. M., Dale, R. A., Bard, E. G., Jeuniaux, P. (2012). Behavior matching in multimodal communication is synchronized. Cognitive Science, 36, 1404-1426.
34. Yang, F., Mo, L., Louwerse, M.M. (2012). Effects of local and global context on processing sentences with subject and object relative clauses. Journal of Psycholinguistic Research, 42, 227-237.
33. Price, K.W., Meisinger, E.B., D’Mello, S.K., Louwerse, M.M. (2012). Silent reading fluency using underlining: Evidence for an alternative method of assessment. Psychology in the Schools, 49, 606–618.
32. Louwerse, M. M. (2011). Stormy seas and cloudy skies: conceptual processing is (still) linguistic and perceptual. Frontiers in Psychology: Cognition, 2, 1-4.
31. Louwerse, M.M. (2011). Symbol interdependency in symbolic and embodied cognition. Topics in Cognitive Science (TopiCS), 3, 273-302.
30. Louwerse, M.M. & Connell, L. (2011). A taste of words: Linguistic context and perceptual simulation predict the modality of words. Cognitive Science, 35, 381-398.
29. Louwerse, M.M. & Bangerter, A. (2010). Effects of ambiguous gestures and language on the time course of reference resolution. Cognitive Science, 34, 1517-1529.
28. Louwerse, M.M. & Jeuniaux, P. (2010). The linguistic and embodied nature of conceptual processing. Cognition, 114, 96-104.
27. McNamara, D.S., Louwerse, M.M., McCarthy, P.M., & Graesser, A.C. (2010). Coh-Metrix: Capturing linguistic features of cohesion. Discourse Processes, 47, 292 – 330.
26. Mitchell, H.H., Graesser, A.C., Louwerse, M.M. (2010). The effect of context on humor: A constraint-based model of verbal jokes. Discourse Processes, 47, 104 – 129.
25. Louwerse, M.M., Graesser, A.C., McNamara, D.S. & Lu, S. (2010). Embodied conversational agents as conversational partners. Applied Cognitive Psychology, 23, 1244 – 1255.
24. Louwerse, M.M. & Zwaan, R.A. (2009). Language encodes geographical information. Cognitive Science, 33, 51-73.
23. Louwerse, M.M. (2008). Embodied representations are encoded in language. Psychonomic Bulletin and Review, 15, 838-844.
22. Louwerse, M.M., Crossley, S., & Jeuniaux, P. (2008). What if? Conditionals in educational registers. Linguistics and Education, 19, 56–69.
21. Louwerse, M.M. (2007). Disambiguating propositions. Revista Signos, 40, 337-356.
20. Crossley, S. A., Louwerse, M., & McNamara, D. S. (2008). Identifying linguistic cues that distinguish text types: A comparison of first and second language speakers. Language Research, 44, 361-381.
19. Crossley, S.A., Louwerse, M.M., McCarthy, P., & McNamara, D.S. (2007). What is an authentic text: A computational analysis of second language reading texts. Modern Language Journal, 91, 15-30.
18. Crossley, S.A. & Louwerse, M.M. (2007). Multi-dimensional register classification using collocations. International Journal of Corpus Linguistics, 12, 453–478.
17. Louwerse, M.M. & Van Peer (2006). Waar het over gaat in cijfers. Kwantitatieve benaderuingen in tekst- en literatuurwetenschap. [What it is about in numbers: quantitative approaches in text- and literary studies]. Tijdschrift voor Nederlandse Taal- en Letterkunde, 122, 21-35.
16. Louwerse, M.M., Cai, Z., Hu, X., Ventura, M., & Jeuniaux, P. (2006). Cognitively inspired natural-language based knowledge representations: Further explorations of Latent Semantic Analysis. International Journal of Artificial Intelligence Tools, 15,1021-1039
15. Graesser, A.C., Cai, Z., Louwerse, M., & Daniel, F. (2006). Question Understanding Aid (QUAID): A web facility that helps survey methodologists improve the comprehensibility of questions. Public Opinion Quarterly, 70, 1-20.
14. Louwerse, M.M. & Ventura, M. (2005). How children learn the meaning of words and how LSA does it (too). Journal of Learning Sciences, 14, 301-309.
13. Louwerse, M.M., Graesser, A.C., Lu, S., & Mitchell, H.H. (2005). Social cues in animated conversational agents. Applied Cognitive Psychology, 19, 1-12.
12. Penumatsa, P., Ventura, M., Graesser, A.C., Franceschetti, D.R., Louwerse, M., Hu, X., Cai, Z., & the Tutoring Research Group (2004). The right threshold value: What is the right threshold of cosine measure when using latent semantic analysis for evaluating student answers? International Journal of Artificial Intelligence Tools, 12, 257-279.
11. Louwerse, M.M. & Kuiken, D. (2004). The effects of personal involvement in narrative discourse. Discourse Processes, 38, 169-172.
10. Louwerse, M.M. (2004). Un modelo conciso de cohesion en el texto y coherencia en la comprehension [A concise model of cohesion in text and coherence in comprehension]. Revista Signos, 37, 41-58.
9. Louwerse, M.M. (2004). Semantic variation in idiolect and sociolect: Corpus linguistic evidence from literary texts. Computers and the Humanities, 38, 207-221.
8. Graesser, A.C., McNamara, D.S., Louwerse, M.M., & Cai, Z. (2004). Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, and Computers, 36, 193-202.
7. Graesser, A.C., Lu, S., Jackson, G.T., Mitchell, H., Ventura, M., Olney, A., & Louwerse, M.M. (2004). AutoTutor: A tutor with dialogue in natural language. Behavioral Research Methods, Instruments, and Computers, 36, 180-193.
6. Louwerse, M.M. & Mitchell, H.H. (2003). Towards a taxonomy of a set of discourse markers in dialog: a theoretical and computational linguistic account. Discourse Processes, 35, 199-239.
5. Louwerse, M.M. (2001). An analytic and cognitive parameterization of coherence relations. Cognitive Linguistics, 12, 291–315.
4. Louwerse, M.M. (1999). Computationele modellen in de literatuurwetenschap: bereken maar! [Computational models in literary studies: Count on it!] Frame, 3, 38-57.
3. Louwerse, M.M. (1999). Computational thematics: Where to start? Journal of Literary Semantics, 28, 1-19.
2. Louwerse, M.M. (1997). Survival of the fittest: kiezen of delen in de literatuurwetenschap [Survival of the fittest: Truth or dare in literary studies]. Frame, 1, 62-71.
1. Louwerse, M.M. (1997). Bits and pieces: Toward an interactive classification of folktales. Journal of Folklore Research, 34, 245-249.
Refereed conference publications
75. Dai, L., Kritskaia, V., van der Velden, E., Jung, M. M., Postma, M., & Louwerse, M. M. (2022, November). Evaluating the usage of text-to-speech in K12 education. In Proceedings of the 2022 6th International Conference on Education and E-Learning (pp. 182-188).
74. Linders, G. M., Vaitonytė, J., Alimardani, M., Mitev, K. O., & Louwerse, M. M. (2022, September). A realistic, multimodal virtual agent for the healthcare domain. In Proceedings of the 22nd ACM International Conference on Intelligent Virtual Agents (pp. 1-3).
73. Guglielmo, G., Wiltshire, T., & Louwerse, M. (2022). Training machine learning models to detect group differences in neurophysiological data using recurrence quantification analysis based features. In 14th International Conference on Agents and Artificial Intelligence (ICAART).
72. van Weelden, E., Wiltshire, T. J., Alimardani, M., & Louwerse, M. M. (2022, September). Comparing presence, workload, and performance in desktop and virtual reality flight simulations. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 66, No. 1, pp. 2006-2010). Sage CA: Los Angeles, CA: SAGE Publications.
71. Van Weelden, E., Alimardani, M., Wiltshire, T. J. & Louwerse, M. M. (2021). Advancing the adoption of virtual reality and neurotechnology to improve flight training. IEEE 2nd International Conference on Human-Machine Systems (ICHMS), 2021, pp. 1-4.
70. van Weelden, E., Wiltshire, T., Alimardani, M., & Louwerse, M. (2021). Validating EEG biomarkers in virtual reality and desktop flight training. In Neuroergonomics Conference 2021.
70. Blomsma, P., Vaitonyte, J., Alimardani, M., & Louwerse, M.M. (2020). Spontaneous facial behavior revolves around neutral facial displays. Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents. Glasgow (p.1-8).
69. Blomsma, P., Linders, G., Vaitonyte, J., & Louwerse, M.M. (2020). Intrapersonal dependencies in multimodal behavior. Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents. Glasgow (p.1-8).
68. Linders, G. & Louwerse, M.M. (2020). Zipf’s Law in Human-Machine Dialog. Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents. Glasgow (p.1-8).
67. Van Limpt-Broers, Postma, M. & Louwerse, M.M. (2020). Awe yields learning: A virtual reality study. Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 488-493). Texas: Austin: Cognitive Science Society.
66. Tinga, A. M., Kuperus, W., Brandao Carvalho, M., Louwerse, M. M. (2019). Explanation versus prediction: Statistical differences in detecting fraudulent events do not necessarily have predictive power. In A. K. Goel, C. M. Seifert, & C. Freska (eds.), Proceedings of the 41th Annual Conference of the Cognitive Science Society (pp. 2975-2980). Montreal, Canada: Cognitive Science Society.
66. Tinga, A. M., Kuperus, W., Brandao Carvalho, M., Louwerse, M. M. (2019). Explanation versus prediction: Statistical differences in detecting fraudulent events do not necessarily have predictive power. In A. K. Goel, C. M. Seifert, & C. Freska (eds.), Proceedings of the 41th Annual Conference of the Cognitive Science Society (pp. 2975-2980). Montreal, Canada: Cognitive Science Society.
65. de Back, T. de, van Hoef, R., Tinga, A., & Louwerse, M.M. (2018). Presence is key: unlocking performance benefits of immersive virtual reality. In Proceedings of 40th Annual Meeting of the Cognitive Science Society (CogSci 2018), Cognitive Science Society.
64. de Back, T., Tinga, A., Van Hoef, R., Peters, E., & Louwerse, M. (2018, July). The applicability and benefits of virtual reality for the cognitive sciences. In Proceedings of 40th Annual Meeting of the Cognitive Science Society (CogSci 2018), Cognitive Science Society.
63. Abney, D., Dale, R., Kello, C., & Louwerse, M.M. (2017). Burstiness across multimodal human interaction reveals differences between verbal and non-verbal communication. In Proceedings of 39th Annual Meeting of the Cognitive Science Society (CogSci 2017), pp. 39-44. Cognitive Science Society.
62. Bernabeu, P., Willems, R., & Louwerse, M.M. (2017). Modality switch effects emerge early and increase throughout conceptual processing: Evidence from ERPs. In Proceedings of 39th Annual Meeting of the Cognitive Science Society (CogSci 2017), pp. 1629-1634. Cognitive Science Society.
61. Carvalho, M.B. & Louwerse, M.M. (2017). Grammar-Based and Lexicon-Based Techniques to Extract Personality Traits from Text. In Proceedings of 39th Annual Meeting of the Cognitive Science Society (CogSci 2017), pp. 1727-1732. Cognitive Science Society.
60. Dinnissen, K. & Louwerse, M.M.(2015). The sound of valence: Phonological features predict word meaning. In D.C. Noelle, R. Dale, A. Warlaumont , J. Yoshimi, T. Matlock, C. D. Jennings, & P.P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 572-577). Austin, TX: Cognitive Science Society.
59. Louwerse, M.M. , Raisig, S., Tillman, R. & Hutchinson, S. (2015). Time after time in words: Chronology through language statistics. In D.C. Noelle, R. Dale, A. Warlaumont , J. Yoshimi, T. Matlock, C. D. Jennings, & P.P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 1428-1433). Austin, TX: Cognitive Science Society.
58. Tillman, R., Hutchinson, S., & Louwerse, M.M. (2015). How sharp is Occam’s razor? Language statistics in cognitive processing. In D.C. Noelle, R. Dale, A. Warlaumont , J. Yoshimi, T. Matlock, C. D. Jennings, & P.P. Maglio (Eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society (pp. 2404-2409). Austin, TX: Cognitive Science Society.
57. Hutchinson, S., Tillman, R., & Louwerse, M. (2014). Quick linguistic representations and precise perceptual representations: Language statistics and perceptual simulations under time constraints. Proceedings of the 36th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
56. Hutchinson, S.C., Wei, L., & Louwerse, M.M. (2014). Avoiding the language-as-a-fixed-effect fallacy: How to estimate outcomes of linear mixed models.In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society . Austin, TX: Cognitive Science Society.
55. Recchia, G., & Louwerse, M. (2014). Grounding the ungrounded: Estimating locations of unknown place names from linguistic associations and grounded representations. Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1270-1275).
54. Recchia, G., Slater, A. L., & Louwerse, M. (2014). Predicting the good guy and the bad guy: Attitudes are encoded in language statistics. Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1264-1269).
53. Datla, V., King-Ip Lin, & Louwerse, M. M. (2014). Part of speech induction from distributional features: balancing vocabulary and context. In Proceedings of the 27th Florida Artificial Intelligence Research Society Conference (pp.28-32). Menlo Park, CA: AAAI Press.
52. Datla, V., King-Ip Lin, & Louwerse, M. M. (2014). Linguistic features predict the truthfulness of short political statements. In A. Gelbukh (ed.), Proceedings of the Conference on Intelligent Text Processing and Computational Linguistics. Berlin: Springer Verlag.
51. Recchia, G. L., & Louwerse, M. M. (2013). A comparison of string similarity measures for toponym matching. Proceedings of ACM SIGSPATIAL CoMP ’13. Orlando, FL: ACM.
50. Hutchinson, S., & Louwerse, M. M. (2013). What’s up can be explained by language statistics. In M. Knauff, M. Pauen, N. Sebanz, & I. Washsmuth (Eds.), In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society . Austin, TX: Cognitive Science Society.
49. Luno, J., Beck, J. G., & Louwerse, M. M. (2013). Tell us your story: Investigating the linguistic features of trauma narrative (pp. 2955-2960). In M. Knauff, M. Pauen, N. Sebanz, & I. Washsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
48. Tillman, R., Hutchinson, S., Jordan, S. & Louwerse, M. M. (2013). Emotion shifts are also language based: An experiment and corpus linguistic study. In M. Knauff, M. Pauen, N. Sebanz, & I. Washsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 3551-3556). Austin, TX: Cognitive Science Society.
47. Tillman, R., Hutchinson, S., & Louwerse, M. M. (2013). Geographical locations are encoded in statistical linguistic frequencies. In M. Knauff, M. Pauen, N. Sebanz, & I. Washsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 3557-3562). Austin, TX: Cognitive Science Society.
46. Hutchinson, S., Datla, V., & Louwerse, M. M. (2012). Social networks are encoded in language. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 491-496). Austin, TX: Cognitive Science Society.;
45. Hutchinson, S., & Louwerse, M. M. (2012). The upbeat of language: Linguistic context and perceptual simulation predict processing valence words. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 1709-1714). Austin, TX: Cognitive Science Society.
44. Louwerse, M. M., Hutchinson, S., & Cai, Z. (2012). The Chinese route argument: Predicting the longitude and latitude of cities in China and the Middle East using statistical linguistic frequencies. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 695-700). Austin, TX: Cognitive Science Society.
43. Tillman, R., Datla, V., Hutchinson, S., & Louwerse, M. M.(2012). From head to toe: Embodiment through statistical linguistic frequencies. In N. Miyake, D. Peebles, & R. P. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society (pp. 2434-2439). Austin, TX: Cognitive Science Society.
42. Lin, K., Datla, V., Morrison, L., & Louwerse, M.M. (2011). Using a feedback system to enhance chart note quality in Electronic Health Records. Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), 649-654.
41. Hutchinson, S., Johnson, S., & Louwerse, M. M. (2011). A linguistic remark on SNARC: Language and perceptual processes in Spatial-Numerical Association. In L. Carlson, C. Hoelscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society (pp.1313-1318). Austin, TX: Cognitive Science Society.
40. Louwerse, M.M., Lin, K., Drescher, A., & Semin, G. (2010). Linguistic cues predict fraudulent events in a corporate social network. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society (pp. 961-966). Austin, TX: Cognitive Science Society.
39. Jeuniaux, P., Dale, R., & Louwerse, M.M. (2009). The role of feedback in learning form-meaning mappings. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31th Annual Conference of the Cognitive Science Society (pp. 1488-1493). Cognitive Science Society.
38. Louwerse, M.M., Benesh, N., Watanabe, S., Zhang, B., Jeuniaux, P., & Vargheese, D. (2009). The Multimodal Nature of Embodied Conversational Agents. In N.A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31th Annual Conference of the Cognitive Science Society (pp. 1459-1463). Cognitive Science Society.
37. Louwerse, M.M. & Jeuniaux, P. (2008). How fundamental is embodiment to language comprehension? Constraints on embodied cognition. In V.Sloutsky, B. Love, & K. McRae (Eds.), In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp.1313-1318). Austin, TX: Cognitive Science Society.
36. Louwerse, M.M., Jeuniaux, P., Zhang, B., Wu, J. & Hoque, M.E. (2008). The interaction between information and intonation structure: Prosodic marking of theme and rheme. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society (pp.1984-1989). Austin, TX: Cognitive Science Society.
35. Louwerse, M.M., Benesh, N., Hoque, M.E., Jeuniaux, P., Lewis, G. , Wu, J., & Zirnstein, M. (2007). Multimodal communication in face-to-face conversations. In D. S. McNamara & J. G. Trafton (Eds.), Proceedings of the 29th Annual Cognitive Science Society (pp. 1235-1240). Austin, TX: Cognitive Science Society.
34. Hoque, M.E., Sorower, M.S., Yeasin, M., & Louwerse, M.M. (2007). What speech tells us about discourse: The role of prosodic and discourse features in dialogue act classification. IEEE International Joint Conference on Neural Networks (IJCNN), 2999-3004.
33. McNamara, D.S., Ozuru, Y., Graesser, A.C., & Louwerse, M. (2006). Validating Coh-Metrix. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 573-578). Mahwah, NJ: Erlbaum.
32. Louwerse, M.M., McNamara, D.S., Graesser, A.C., Lewis, G., & Zirnstein, M. (2006). An eye for an eye, and for other modalities. In Silva, M. & Cox, A. (Eds.), Proceedings of the Cognitive Science Workshop “What have eye movements told us so far, and what is next?” London, University College London.
31. Louwerse, M.M., Jeuniaux, P., Hoque, M.E., Wu, J., & Lewis, G. (2006). Multimodal communication in computer-mediated map task scenarios. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1717-1722). Mahwah, NJ: Erlbaum.
30. Louwerse, M.M., Graesser, A.C., McNamara, D.S., Jeuniaux, P., & Yang, F. (2006). Coherence is also in the eye of the beholder. In Silva, M. & Cox, A. (Eds.), Proceedings of the Cognitive Science Workshop “What have eye movements told us so far, and what is next?” London, University College London.
29. Jeuniaux, P., Louwerse, M.M., & Hu, X. (2006). The role of discourse structure and response time in multimodal communication. In Gratch, J., Young, M., Aylett, R., Ballin, D., & Olivier, P. (Eds.), Proceedings of the 6th International Conference in Intelligent Virtual Agents (pp. 459-460). New York, Springer.
28. Hoque, M.E., Yeasin, M., & Louwerse, M.M. (2006). Robust recognition of emotion from speech. In Gratch, J., Young, M., Aylett, R., Ballin, D., & Olivier, P. (Eds.), Proceedings of the 6th International Conference in Intelligent Virtual Agents (pp. 42-53). New York, Springer.
27. Guhe, M., Steedman, M., Bard, E.G., & Louwerse, M.M. (2006). Prosodic marking of contrasts in information structure. In Schlangen, D. (Ed.), Brandial ’06 Proceedings of the 10th Workshop on the Semantics and Pragmatics of Dialogue (SemDial-10) (pp.179-180). Potsdam: Univ. Verlag.
26. Dufty, D.F., Graesser, A.C., Louwerse, M., & McNamara, D.S., (2006). Is it just readability, or does cohesion play a role? In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1251-1256). Mahwah, NJ: Erlbaum.
25. Crossley, S.A., McCarthy, P.M., Lewis, G.A., Dufty, D.F., Louwerse, M.M., & McNamara, D.S. (2006). Detecting manipulated texts. In R. Sun & N. Miyake (Eds.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (p. 2463). Mahwah, NJ: Erlbaum.
24. Louwerse, M.M. & Crossley, S.A. (2006). Dialog act classification using n-gram algorithms. In Proceedings of the 19th International Florida Artificial Intelligence Research Society.
23. Louwerse, M.M., Cai, Z., Hu, X., Ventura, M., & Jeuniaux, P. (2005). The embodiment of amodal symbolic knowledge representations. In I. Russell & Z. Markov (Eds.), Proceedings of the 18th International Florida Artificial Intelligence Research Society (pp. 542-547). Menlo Park, CA: AAAI Press.
22. Louwerse, M.M. & Bangerter, A. (2005). Focusing attention with deictic gestures and linguistic expressions. In B. Bara, L. Barsalou, & M. Bucciarelli (Eds.), Proceedings of the Cognitive Science Society (pp. 1331-1336). Mahwah, NJ: Lawrence Erlbaum.
21. Ventura, M., Hu, X., Graesser, A., & Louwerse, M. (2004). The context dependent sentence abstraction model. In K. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the twenty-sixth annual conference of the Cognitive Science Society (pp. 1387-1392). Mahwah, NJ: Erlbaum.
20. McNamara, D.S., Floyd, R.G., Best, R., & Louwerse, M. (2004). World knowledge driving young readers’ comprehension difficulties. In Y.B. Yasmin, W.A., Sandoval, N. Enyedy, A.S. Nixon, & F. Herrera (Eds.), Proceedings of the sixth international conference of the learning sciences: Embracing diversity in the learning sciences (pp. 326-333). Mahwah, NJ: Erlbaum.
19. Louwerse, M.M., McCarthy, P.M., McNamara, D.S., & Graesser, A.C. (2004). Variation in language and cohesion across written and spoken registers. In K. Forbus, D. Gentner, & T. Regier (Eds.), Proceedings of the twenty-sixth annual conference of the Cognitive Science Society (pp. 843-848). Mahwah, NJ: Erlbaum.
18. Howell, K., Cannon-Bowers, J., Corbett, A., Louwerse, M.M., & Moye, A. (2004). Learning Science and technology R&D: A roadmap to the future of learning. Proceedings for the Frontiers in Education (FIE) 2004 Conference. CD-ROM.
17. Dufty, D.F., McNamara, D., Louwerse, M., Cai, Z., & Graesser, A.C. (2004). Automated evaluation of aspects of document quality. In S. Tilley & S. Huang (Eds.), Proceedings of the 22nd annual international conference on Documentation (pp. 14-16). New York, ACM.
16. Cai, Z., McNamara, D. S., Louwerse, M. M., Hu, X., Rowe, M. P., & Graesser, A.C. (2004). NLS: A non-latent similarity algorithm. In K. D. Forbus, D. Gentner, T. Regier (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 180-185). Mahwah, NJ: Erlbaum.
15. Olney , A., Louwerse, M., Mathews, E., Marineau, J., Hite-Mitchell, H., & Graesser, A. (2003). Utterance Classification in AutoTutor. In J. Burstein & C. Leacock (Eds.), Building Educational Applications using Natural Language Processing: Proceedings of the Human Language Technology – North American Chapter of the Association for Computational Linguistics Conference 2003 Workshop, May 31, (pp. 1-8). Philadelphia: Association for Computational Linguistics.
14. Louwerse, M.M., Graesser, A.C., & the Tutoring Research Group (2003). Language use in intelligent tutoring systems: mixed-initiative dialog in AutoTutor. In A.K. Noor (Ed.), Proceedings of workshop on Advanced learning technologies and learning networks and their impact on future aerospace workforce (pp. 251-276). Hanover, MD: NASA Center for Aerospace Information (NASA/CP-2003-212437).
13. Hu, X., Cai, Z., Franceschetti, D., Penumatsa,P., Graesser, A.C., Louwerse, M.M., McNamara, D.S., & TRG (2003). LSA: The first dimension and dimensional weighting. In R. Alterman and D. Hirsh (Eds.), Proceedings of the 25th Annual Conference of the Cognitive Science Society (pp. 587-592). Boston, MA: Cognitive Science Society.
12. Hu, X., Cai, Z., Graesser, A.C., Louwerse, M.M., Penumatsa, P., Olney, A. & the Tutoring Research Group (2003). An improved LSA algorithm to evaluate student contributions in tutoring dialogue. In G. Gottlob & T. Walsh (Eds.), Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (pp.1489-1491). San Francisco: Morgan Kaufmann.
11. Graesser, A.C., Jackson, G.T., Mathews, E.C., Mitchell, H.H., Olney, A., Ventura, M., Chipman, P., Franceschetti, D., Hu, X., Louwerse, M.M., Person, N.K., & TRG (2003). Why/AutoTutor: A test of learning gains from a physics tutor with natural language dialog. In R. Alterman & D. Hirsh (Eds.), Proceedings of the 25th Annual Conference of the Cognitive Science Society (pp. 1-5). Boston, MA: Cognitive Science Society.
10. Olney, A., Person, N., Louwerse, M., & Graesser, A. (2002). AutoTutor: A conversational tutoring environment. Proceedings of the ACL-02 Demonstration Session (pp. 108–109). Philadelphia: Association for Computational Linguistics.
9. Marineau, J., Olney, A., Louwerse, M., Person, N., Olde, B., Susarla, S., Chipman, P., Graesser, A.C., & TRG (2002). AutoTutor’s log files and categories of language and discourse. In C.P. Rose & V. Eleven (Eds.), Workshop Proceedings of Empirical Methods for Tutorial Dialogue Systems at IRS 2002 (pp. 85-92). San Sebastian, Spain.
8. Louwerse, M.M., Graesser, A.C., Olney, A., & the Tutoring Research Group (2002). Good computational manners: Mixed-initiative dialog in conversational agents. In C. Miller, Etiquette for Human-Computer Work. Papers from the 2002 Fall Symposium, Technical Report FS-02-02 (pp. 71-76). Menlo Park, CA: AAAI Press.
7. Louwerse, M., Graesser, A., Hu, X., & Person, N. (2002). The role of intelligent tutoring systems in education: An overview of AutoTutor. In C. Crawford et al. (Eds.), Proceedings of Society for Information Technology and Teacher Education International Conference 2002 (pp. 2056-2057). Chesapeake, VA: AACE.
6. Jackson, T., Mitchell, H.H., Graesser, A.C., & Louwerse, M. (2002). Improving conversational interaction for intelligent tutoring systems. The 4th Annual Memphis Area Engineering and Science Conference Proceedings.
5. Graesser, A.C., Hu, X., Olde, B.A., Ventura, M., Olney, A., Louwerse, M., Franceschetti, D.R., & Person, N. (2002). Implementing latent semantic analysis in learning environments with conversational agents and tutorial dialog. . In W.G. Gray and C.D. Schunn (Eds.) Proceedings of the 24th Annual Meeting of the Cognitive Science Society (p. 37). Mahwah, NJ: Erlbaum.
4. Louwerse, M.M. (2001). Context in causal and diagnostic readings: Cognitive evidence from eye tracking. In: Degand, L., Bestgen, Y., Spooren, W., & Waes, L. (Eds.). Multidisciplinary Approaches to Discourse (pp. 11-26). Amsterdam & Muenster, Uitgaven Stichting Neerlandistiek VU, Nodus.
3. Graesser, A.C., Karnavat, A.B., Daniel, F.K., Cooper, E., Whitten, S.N., & Louwerse, M. (2001). A computer tool to improve questionnaire design. In Statistical Policy Working Paper 33, Federal Committee on Statistical Methodology (pp. 36-48). Washington, DC: Bureau of Labor Statistics.
2. Graesser, A.C., Hu, X., Susarla, S., Harter, D., Person, N., Louwerse, M., Olde, B., & the TRG (2001). AutoTutor: An intelligent tutor and conversational tutoring scaffold. Papers from the Workshop on ‘Tutorial Dialog Systems’ at the Artificial Intelligence in Education 2001 Conference (pp.47-49). San Antonio, TX.
1. Louwerse, M.M. (1999). The source of coherence: Why semantic vs. pragmatic is not part of a cognitive approach to a parameterisation of coherence relations. Working notes. International Workshop on Text Representation (pp. 55-61). University of Edinburgh, July 7-9 1999.
Book chapters
18. Graesser, A.C., McNamara, D.S., & Louwerse, M.M. (2011). Methods of automated text analysis. In R. Barr, M.L. Kamil, P.B. Mosenthal, and P.D. Pearson (Eds.), Handbook of reading research (pp. 34-53). New York: Routledge.
17. Louwerse, M.M., & Jeauniaux, P. (2009). Computational psycholinguistic techniques to measure cohesion in discourse. In J. Renkema (Ed.), Discourse of course (pp. 213-223). Amsterdam: Benjamins.
16. Louwerse, M.M., Benesh, N., Zhang, B. (2008). Computationally discriminating literary from non-literary texts. In S. Zyngier, M. Bortolussi, A. Chesnokova, J. Auracher (Eds.), Directions in empirical literary studies (pp.175-192). Amsterdam: Benjamins.
15. Louwerse, M.M. & Van Peer, W. (2009). Incorporated means symbolic and embodied. Reply to Geeraerts. In Brone, G. & Vandaele, J. (Eds.), Cognitive poetics (pp. 451-454). Berlin, Germany: De Gruyter.
14. Louwerse, M.M. & Van Peer, W. (2009). How cognitive is cognitive poetics? The interaction between symbolic and embodied cognition. In Brone, G. & Vandaele, J. (Eds.), Cognitive Poetics (pp. 423-444). Berlin, Germany: De Gruyter.
13. Louwerse, M.M., Lewis, G. & Wu, J. (2008). Unigrams, bigrams and LSA. Corpus linguistic explorations of genres in Shakespeare’s plays. In Van Peer, W. & Auracher, J. (eds). New directions in literary studies (pp.108-129). Newcastle: Cambridge Scholars Publishing.
12. Louwerse, M. M., & Jeuniaux, P. (2008). Language comprehension is both embodied and symbolic. In M. de Vega, A. Glenberg, & A. C. Graesser (Eds.), Embodiment and meaning: A debate (pp. 309-326). Oxford: Oxford University Press.
11. Vanderveen, A., Huff, K., Gierl, M., McNamara, D.S., Louwerse, M.M., & Graesser, A.C. (2007). Developing and validating instructionally relevant reading competency profiles measured by the critical reading section of the SAT. In McNamara, D.S. (Ed.), Reading comprehension strategies: Theory, interventions, and technologies (pp. 137-172). Mahwah, NJ: Erlbaum.
10. Graesser, A.C., Louwerse, M.M., McNamara, D., Olney, A., Cai, Z., & Mitchell, H. (2007). Inference generation and cohesion in the construction of situation models: Some connections with computational linguistics. In F. Schmalhofer and C. Perfetti (Eds.), Higher level language processes in the brain: Inferences and comprehension processes (pp. 289-310). Mahwah, NJ: Erlbaum.
9. McNamara, D.S., Cai, Z., & Louwerse, M.M. (2007). Comparing latent and non-latent measures of cohesion. In T. Landauer, D.S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of latent semantic analysis (pp. 379-400). Mahwah, NJ: Erlbaum.
8. Louwerse, M.M. (2007). Symbolic or embodied representations: A case for symbol interdependency. In T. Landauer, D. McNamara, S. Dennis, & W. Kintsch (Eds.). Handbook of latent semantic analysis (pp. 107-120). Mahwah, NJ: Erlbaum.
7. Louwerse, M.M. & Van Peer, W. (2006). Thematics. In: Keith Brown, (Editor-in-Chief) Encyclopedia of Language & Linguistics, Second Edition, 12 (pp. 653-658). Oxford: Elsevier.
6. Louwerse, M.M. & Graesser, A.C. (2006), Macrostructure. In: Keith Brown, (Editorin-Chief) Encyclopedia of Language & Linguistics, Second Edition, 7 (pp. 426-429). Oxford: Elsevier.
5. Louwerse, M.M. & Graesser, A.C. (2005). Coherence in discourse. In Strazny, P. (ed.), Encyclopedia of linguistics. (pp. 216-218). Chicago: Fitzroy Dearborn.
4. Graesser, A.C., McNamara, D.S., & Louwerse, M.M. (2003). What do readers need to learn in order to process coherence relations in narrative and expository text. In A.P. Sweet and C.E. Snow (Eds.), Rethinking reading comprehension (pp. 82-98). New York: Guilford Publications.
3. Louwerse, M.M. & Van Peer, W. (2002). Introduction. In M. M. Louwerse & W. van Peer (eds.), Thematics: Interdisciplinary Studies (pp. 1-17). Amsterdam/Philadelphia, John Benjamins.
2. Louwerse, M.M. (2002). Computational retrieval of themes. In M. M. Louwerse & W. van Peer (eds.), Thematics: Interdisciplinary studies (pp. 189-212). Amsterdam/Philadelphia, John Benjamins.
1. Louwerse, M.M. (1997). Inleiding [Introduction]. In Vladimir Propp, De morfologie van het toversprookje. Vormleer van een genre [The Morphology of the Folktale. Formal Study of a Genre; transl. M. M. Louwerse]. Utrecht, Het Spectrum.
Nonrefereed publications
2. Ryder, J.M., Graesser, A.C., Le Mentec, J.-C., Louwerse, M.M., Karnavat, A., Popp, E.A., & Hu, X. (2004). A Dialog-based Intelligent Tutoring System for Practicing Battle Command Reasoning. Army Research Institute Technical Report). Alexandria, VA: US Army Research Institute for the Behavioral and Social Sciences.
1. Graesser, A.C., Louwerse, M.M., Burger, J., Carroll, J. et al. (2003). Question generation and answering systems: R&D for technology-enabled learning systems. Research roadmap for Federation of American Sciences.