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Grant: Along with PI R. Stuart Geiger (University of California, Berkeley) and fellow co-PI Lilly Irani (Lilly Irani, University of California, San Diego), our team won an interdisciplinary grant from the Ford and Ford Foundations to help our understanding of important digital infrastructure. Check out the announcement from Ford below!
Outreach: Videos and code from the Data on the Mind 2017 summer workshop are now available! Check out 11 tutorials dedicated to helping cognitive scientists explore questions about cognition and behavior with big and naturally occurring data. Find out more through the links below.
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Paxton, A., & Dale, R. (2013). B(eo)W(u)LF: Facilitating recurrence analysis on multi-level language. arXiv:1308.2696 [cs.CL].
Paxton, A., Dale, R., & Richardson, D. C. (2016). Social coordination of verbal and nonverbal behaviors. In P. Passos, K. Davids, and C. Jia Yi (Eds.), Interpersonal coordination and performance in social systems. Routledge. https://alexandrapaxton.com/files/paxton_dale_richardson-2016-icpss.pdf
Richardson, M. J., Paxton, A., & Kuznetsov, N. (2017). Nonlinear methods for understanding complex dynamical phenomena in psychological science. Psychological Science Agenda.
Paxton, A. (2019). #PSBigData: Helping big data research become more ethical and more open. Psychonomic Society Featured Content.
Paxton, A. (2020). The Belmont Report in the age of big data: Ethics at the intersection of psychological science and data science. In S. E. Woo, L. Tay, & R. Proctor (Eds.), Big data methods for psychological research: New horizons and challenges (pp. 347-372). American Psychological Association. doi: 10.1037/0000193-016 https://alexandrapaxton.com/files/paxton-belmont_report_in_big_data-accepted.pdf
From Paxton & Dale (2013). Resources for automated frame-differencing method (FDM) for analyzing interpersonal bodily synchrony, with sample MATLAB code for the FDM and AppleScript for preparing image segmentation. Be sure to save the AppleScript in the appropriate format before use. http://a-paxton.github.io/files/paxton_dale-2013-brm.pdf
From Tollefsen, Dale, & Paxton (2013). Color version of Figure 1, presenting body movement in colored lines and speech events as shaded boxes of corresponding color. Code to create these plots with your own data is available on GitHub. http://a-paxton.github.io/files/tollefsen_paxton_dale-2013-rpp.pdf
Abney, D., Paxton, A., Kello, C.T., & Dale, R. (2013). Complexity matching in dyadic interaction. In P. Passos, J. Barrieros, R. Cordovil, D. Araújo, & F. Melo (Eds.), Studies in Perception and Action XII. Proceedings from the Seventeenth International Conference on Perception and Action.
Paxton, A., & Dale, R. (2013). Multimodal networks for interpersonal interaction and conversational contexts. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Roche, J. M., Paxton, A., Ibarra, A., & Tanenhaus, M. K. (2013). From minor mishap to major catastrophe: Lexical choice in miscommunication. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Paxton, A., Abney, D., Kello, C. K., & Dale, R. (2014). Network analysis of multimodal, multiscale coordination in dyadic problem solving. In P. M. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Paxton, A., & Dale, R. (2014). Leveraging linguistic content and debater traits to predict debate outcomes. In P. M. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Paxton, A., Roche, J. M., Ibarra, A., & Tananhaus, M. K. (2014). Failure to (mis)communicate: Linguistic convergence, lexical choice, and communicative success in dyadic problem solving. In P. M. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Paxton, A.*, Roche, J.*, & Tanenhaus, M. (2015). Communicative efficiency and miscommunication: The costs and benefits of variable language production. In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings, & P. P. Maglio (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Paxton, A., Morgan, T. J. H., Suchow, J. W., & Griffiths, T.L. (2018). Interpersonal coordination of perception and memory in real-time online social experiments. In Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Blau, J. J. C., & Paxton, A. (2019). Scale-independent aggression. In L. van Dijk and R. Withagen (Eds.), Studies in Perception and Action XX: Proceedings from the Twentieth International Conference on Perception and Action. Enschede: Ipskamp Printing.
Chiovaro, M., & Paxton, A. (2019). Nest-ed affordances. In L. van Dijk and R. Withagen (Eds.), Studies in Perception and Action XX: Proceedings from the Twentieth International Conference on Perception and Action. Enschede: Ipskamp Printing.
Paxton, A., Blau, J. J. C., & Weston, M. (2019). The case for intersectionality in ecological psychology. In L. van Dijk and R. Withagen (Eds.), Studies in Perception and Action XX: Proceedings from the Twentieth International Conference on Perception and Action. Enschede: Ipskamp Printing.
Pouw, W., Paxton, A., Harrison, S. J., & Dixon, J. (2019). Acoustic specification of upper limb movement in voicing. In A. Grimminger (Ed.), Proceedings of the 6th Gesture and Speech in Interaction. Paderborn: Universitaetsbibliothek Paderborn.
Pouw, W., de Jonge-Hoekstra, L., Harrison, S. J., Paxton, A., & Dixon, J. (2020). Gesture-speech physics in fluent speech and rhythmic upper limb movements. In A. Grimminger (Ed.), Proceedings of the 7th Gesture and Speech in Interaction. Paderborn: Universitaetsbibliothek Paderborn.
Chiovaro, M., Windsor, L. C., & Paxton, A. (2019). Vector autoregression, cross-correlation, and cross-recurrence quantification analysis: A case study in social cohesion and collective action. In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Sharmin, S., Ivan, J. N., Kerry, M. L., Paxton, A., & Tucker, A. (forthcoming, 2022). Driver psychology latent classes as predictors of traffic incident occurrence in Naturalistic Driving Study (NDS) data. To appear in Proceedings of the Transportation Research Board 2022 Annual Meeting. Washington, D.C.: National Academies of Sciences, Engineering, and Medicine.
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Paxton, A., & Dale, R. (2013). Frame-differencing methods for measuring bodily synchrony in conversation. Behavior Research Methods, 45(2), 329-343. http://a-paxton.github.io/files/paxton_dale-2013-brm.pdf
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Paxton, A., & Dale, R. (2013). Argument disrupts interpersonal synchrony. Quarterly Journal of Experimental Psychology, 66(11), 2092-2102. http://a-paxton.github.io/files/paxton_dale-2013-qjep.pdf
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Tollefsen, D., Dale, R., & Paxton, A. (2013). Alignment, transactive memory, and collective cognitive systems. Review of Philosophy and Psychology, 4(1), 49-64. http://a-paxton.github.io/files/tollefsen_paxton_dale-2013-rpp.pdf
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Abney, D., Paxton, A., Dale, R., & Kello, C.T. (2014). Complexity matching in dyadic interaction. Journal of Experimental Psychology: General, 143(6), 2304-2315. http://a-paxton.github.io/files/abney_paxton_dale_kello-2014-jepg.pdf
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Abney, D., Paxton, A., Dale, R., & Kello, C. (2015). Movement dynamics reflect a functional role for weak coupling and role structure in dyadic problem solving. Cognitive Processing, 16(4), 325-332. http://a-paxton.github.io/files/abney_paxton_dale_kello-2015-cp.pdf
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Fusaroli, R., Perlman, M., Mislove, A., Paxton, A., Matlock, T., & Dale, R. (2015). Timescales of massive human entrainment. PLOS ONE, 10(4), e0122742. http://a-paxton.github.io/files/fusaroli_et_al-2015-plos.pdf
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Paxton, A., Rodriguez, K., & Dale, R. (2015). PsyGlass: Capitalizing on Google Glass for naturalistic data collection. Behavior Research Methods, 47(3), 608-619. http://a-paxton.github.io/files/paxton_rodriguez_dale-2015-brm.pdf
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Main, A., Paxton, A., & Dale, R. (2016). An exploratory analysis of dynamic emotion regulation between mothers and adolescents during conflict discussions. Emotion, 16(6), 913-928. http://a-paxton.github.io/files/main_paxton_dale-2016-emotion.pdf
Published in Frontiers in Psychology, 1900
Paxton, A., & Dale, R. (2017). Interpersonal movement synchrony responds to high- and low-level conversational constraints. Frontiers in Psychology, 8, 1135.
Published in Behavior Research Methods, 1900
Paxton, A., & Griffiths, T. L. (2017). Finding the traces of behavior and cognition in big data and naturally occurring datasets. Behavior Research Methods, 49(5), 1630–1638.
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Smith, G. K., Mills, C., Paxton, A., & Christoff, K. (2018). Mind wandering rates fluctuate across the day: Evidence from an experience sampling study. Cognitive Research: Principles & Implications, 3, 54. doi: 10.1186/s41235-018-0141-4 https://doi.org/10.1186/s41235-018-0141-4
Published in Psychological Methods, 1900
Duran, N., Paxton, A., & Fusaroli, R. (2019). ALIGN: Analyzing Linguistic Interactions with Generalizable techNiques. Psychological Methods, 24(4), 419-438. doi: 10.1037/met0000206 https://doi.org/10.1037/met0000206
Published in Policy Insights from the Behavioral and Brain Sciences, 1900
Paxton, A., & Tullett, A. (2019). Open science in data-intensive psychology and cognitive science. Policy Insights from the Behavioral and Brain Sciences, 6(1), 47-55. doi: 10.1177/2372732218790283. https://doi.org/10.1177/2372732218790283
Published in Complexity, 1900
Blau, J. J. C., & Paxton, A. (2020). Scale-independent aggression: A fractal analysis of four levels of human aggression. Complexity, 2020, 2047157.
Published in PLOS Computational Biology, 1900
DeMasi, O.*, Paxton, A.*, & Koy, K. (2020). Ad hoc efforts for advancing data science education. PLOS Computational Biology, 16(5), e1007695. doi: 10.1371/journal.pcbi.1007695
Published in Cognitive Science, 1900
Müller-Frommeyer, L. C., Kauffeld, S., & Paxton, A. (2020). Beyond consistency: Contextual dependency of language style in monologue and conversation. Cognitive Science, 44(4), e12834. doi: 10.1111/cogs.12834
Published in Ecological Psychology, 1900
Chiovaro, M., & Paxton, A. (2020). Action coordination in non-human self-organizing collectives: Multidisciplinary lessons from living and nonliving systems. Ecological Psychology, 32(4), 139-142. doi: 10.1080/10407413.2020.1842136
Published in Proceedings of the National Academy of Sciences, 1900
Pouw, W., Paxton, A., Harrison, S. J., & Dixon, J. (2020). Acoustic information about upper limb movement in voicing. Proceedings of the National Academy of Sciences, 117(21), 11364-11367. doi: 10.1073/pnas.2004163117.
Published in Ecological Psychology, 1900
Chiovaro, M., & Paxton, A. (2020). Ecological psychology meets ecology: Apis mellifera as a model for perception-action, social dynamics, and human factors. Ecological Psychology, 32(4), 192-213. doi: 10.1080/10407413.2020.1836966
Published in Proceedings of the National Academy of Sciences, 1900
Pouw, W., Paxton, A., Harrison, S. J., & Dixon, J. (2020). Reply to Ravignani and Kotz: Physical impulses from upper-limb movements impact the respiratory-vocal system. Proceedings of the National Academy of Sciences, 117(38), 23225-23226. doi: 10.1073/pnas.2015452117
Published in Journal of Experimental Psychology: General, 1900
Abney, D., Paxton, A., Dale, R., & Kello, C. (2021). Cooperation in sound and motion: Complexity matching in collaborative interaction. Journal of Experimental Psychology: General, 150(9), 1760-1771. doi: 10.1037/xge0001018
Published in PLOS ONE, 1900
Chiovaro, M., Windsor, L. C.*, Windsor, A., & Paxton, A.* (2021). Online social cohesion reflects real-world group action in Syria during the Arab Spring. PLOS ONE, 16(7), e0254087. doi: 10.1371/journal.pone.0254087
Published in Journal of Experimental Psychology: General, 1900
De Bari, B., Paxton, A., Dixon, J. A., Kondepudi, D., & Kay, B. A. (2021). Functional interdependence in coupled dissipative structures: Physical foundations of biological intra- and inter-organism. Entropy, 23(5), 614. doi: 10.3390/e23050614
Published in Journal of Speech, Language, and Hearing Research, 1900
Paxton, A.*, Roche, J. M.*, Ibarra, A., & Tanenhaus, M. K. (2021). Predictions of miscommunication in verbal communication during collaborative joint action. Journal of Speech, Language, and Hearing Research, 64(2), 613-627. http://a-paxton.github.io/files/paxton_roche_ibarra_tanenhaus-2021-jslhr.pdf
Published in Annals of the New York Academy of Sciences, 1900
Pouw, W., de Jonge-Hoekstra, L., Harrison, S. J., Paxton, A., & Dixon, J. (2021). Gesture-speech physics in fluid speech and rhythmic hand movement. Annals of the New York Academy of Sciences, 1491(1), 89-105. doi: 10.1111/nyas.14532
Published in Acta Psychologica, 1900
Romero, V., & Paxton, A. (2021). Visual information and communication context as modulators of interpersonal coordination in face-to-face and videoconference-based interactions [Registered report]. Acta Psychologica, 221, 103453. doi: 10.1016/j.actpsy.2021.103453
Published in Journal of Developmental and Physical Disabilities, 1900
Schwab, S. M., Carver, N. S., Forman, M., Abney, D. H., Davis, T. J., Riley, M. A., Paxton, A., & Silva, P. L. (2022). Child-caregiver interactions during a collaborative motor task in children with cerebral palsy: A descriptive exploratory study. Journal of Developmental and Physical Disabilities, 34, 255-277. doi: 10.1007/s10882-021-09798-6 http://a-paxton.github.io/files/schwab_et_al-2022-jdpd.pdf
Published in Cognitive Science, 1900
Paxton, A., Varoquaux, N., Holdgraf, C., & Geiger, R. S. (accepted). Community, time, and (con)text: Online communication patterns in open-source software communities and their implications for community health. Cognitive Science.
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Jiang, S., Paxton, A., Ramírez-Esparza, N., & García-Sierra, A. (submitted). Toward a dynamic approach of person perception at zero acquaintance: Applying recurrence quantification analysis to thin slices.
Published in , 1900
Chiovaro, M., & Paxton, A. (under revision). Natural, nonlinear, and noisy: A quantitative approach to the collection and analysis of real-world social behavior.
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Hall, C., Kim, J. C., & Paxton, A. (under revision). Multidimensional recurrence quantification analysis of human-metronome phasing.
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Mankovich, A., Wittke, K., Blume, J., Mastergeorge, A. M., Paxton, A., & Naigles, L. R. (in preparation). Say that again: Quantifying patterns of grammatical production for children with ASD using recurrence analysis.
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Paxton, A., Richardson, D. C., & Dale, R. (in preparation). Seeing the other side: Conflict and controversy increase gaze coordination.
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Xi, Q., Chiovaro, M., Windsor, L. C., & Paxton, A. (in preparation). Online emotion diffusion and its coupling with real-world collective action in Syria during the Arab Spring [Registered report].
Publication: Humans are a kind of dissipative structure---that is, an entity that requires the addition of energy in order to sustain itself. Recently, Ben de Bari led a project in which we investigated seemingly social behavior of nonliving dissipative structures, allowing us to explore how much of our human social dynamics might be explained by the constraints and pressures of being dissipative structures in shared environments (De Bari, Paxton, Kondepudi, Kay, & Dixon, 2021, Entropy).
Data ethics: Psychological scientists are increasingly interested in harnessing big data and naturally occurring data, but this new data landscape poses new challenges. I argue that the Belmont principles of respect for persons, beneficence, and justice can---and should!---serve as our ethical foundation as we deal with human-derived data (Paxton, 2020, Big data methods for psychological research: New horizons and challenges). https://alexandrapaxton.com/files/paxton-belmont_report_in_big_data-accepted.pdf
Publication: Graduate student Megan Chiovaro led an interdisciplinary collaboration exploring the connection between online and offline social cohesion by analyzing real-world action and Twitter activity during the Arab Spring (Chiovaro, L. C. Windsor*, A. Windsor, & Paxton*, 2021, PLOS ONE).
Methods development: Automatically and reproducibly quantify multi-level linguistic alignment in natural conversation with ALIGN (Duran, Paxton, & Fusaroli, 2019, Psychological Methods). Find our Python package on GitHub, or install it directly from PyPI! https://doi.org/10.1037/met0000206
Conference proceedings: We argue that ecological psychology must grow to consider how intersectionality (Crenshaw, 1991) impacts social effectivities and social affordances (Paxton, Blau, & Weston, 2019, Studies in Perception and Action XV: Proceedings from the Twentieth International Conference on Perception and Action).
ALIGN. Python library for extracting quantitative, reproducible metrics of multi-level alignment between two speakers in naturalistic language corpora.
bwlf. Code to help get text data into recurrence-ready analysis form. Development supported by the NSF under grants BCS-0826825 and BCS-0926670.
clustering-tutorial. Tutorial for k-means clustering in R, with lessons on good coding practices and the tidyverse along the way.
crqa-tools. Tutorials and tools to help with RQA and CRQA in R. Currently includes tutorials on continuous and categorical RQA and CRQA, along with tools to help with plotting.
Data on the Mind. A community resource dedicated to helping bridge the gaps between big data and cognitive science.
Data on the Mind 2017 workshop. Materials from Data on the Mind's 2017 summer workshop, aimed at providing early-career researchers in cognitive science and psychology with hands-on introductions to essential data science skills. Exercises and tutorial videos are provided below. Generously funded by the Estes Fund, Berkeley's D-Lab, and Project Jupyter.
Frame-differencing method. MATLAB code for measuring body movement and interpersonal synchrony from videos. Development supported by the NSF under grants BCS-0826825 and BCS-0926670. http://a-paxton.github.io/files/paxton_dale-2013-brm.pdf
Gensim-LSI-Word-Similarities. Functions to calculate various similarity scores from Gensim's latent semantic indexing in Python.
living-documents. A tutorial on using Jupyter notebooks and R markdown to create living documents, reproducible reports, and reproducible manuscripts. Includes Binder-based demonstration to get you started (nearly) instantly.
NODS in psychological research. Repository of exercises and code associated with my Spring 2021 class, "Naturally occurring data in psychological research" (PSYC 5570).
plotting-coupled-data. Code plots coupled categorical and continuous time series in a single, elegant plot. It was originally created to visualize concurrent speech (categorical) and movement (continuous) signals in the same plot.
professional-website-design. Tutorial on creating a professional website on GitHub Pages.
PsyGlass. Code to enable researchers to turn Google Glass into a tool for experiment design and data collection. http://a-paxton.github.io/files/paxton_rodriguez_dale-2015-brm.pdf
stats-tools. Bits of code to help clean up and display statistical analyses, largely in R.
xsede-quickstarts. A few quickstart guides to getting going on XSEDE resources (Jetstream and PSC Bridges). In addition to walkthroughs, it also includes some basic scripts that you can use as templates to help manage your instances.
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Undergraduate course, University 1, Department, 2014
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