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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.
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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/2013-paxton_dale-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. (2013). 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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Duran, N., Paxton, A., & Fusaroli, R. (accepted). ALIGN: Analyzing Linguistic Interactions with Generalizable techNiques. Psychological Methods.
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Paxton, A., Richardson, D. C., & Dale, R. (in preparation). Seeing the other side: Conflict and controversy increase gaze coordination.
Published in Policy Insights from the Behavioral and Brain Sciences, 1900
Paxton, A., & Tullett, A. (in press). Open science in data-intensive psychology and cognitive science. Policy Insights from the Behavioral and Brain Sciences.
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Smith, G. K., Mills, C., Paxton, A., & Christoff, K. (accepted). Mind wandering rates fluctuate across the day: Evidence from an experience sampling study. Cognitive Research: Principles & Implications.
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.
Improving public policy: Open science can be transformative to data-intensive psychology and cognitive science, and US policy makers can help foster the adoption of open-science policies (Paxton & Tullett, in press, Policy Insights from the Behavioral and Brain Sciences). Read our preprint here!
Conference proceedings: Explore the emergence of perceptual and memory coordination during minimally interactive (online) contexts (Paxton, Morgan, Suchow, & Griffiths, 2018, Proceedings of the Cognitive Science Society). Read our proceedings paper, and check out the code for our experiment and analyses on our GitHub repository!
Methods development: Automatically and reproducibly quantify multi-level linguistic alignment in natural conversation with ALIGN (Duran, Paxton, & Fusaroli, accepted, Psychological Methods). Find our Python package on GitHub, or install it directly from PyPI. Read about it in our preprint on PsyArXiv!
Call to action: Use big or naturally occurring data sets (BONDS) to test theories outside the lab by finding the traces of the behavioral and cognitive processes within the human-generated data (Paxton & Griffiths, 2017, Behavior Research Methods). Read the open-access article!
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.
crqa-tools. Some bits of code to help with CRQA plotting in R.
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 and reproducible reports.
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.
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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Workshop, University 1, Department, 2015
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