- Nov 2022
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www.researchgate.net www.researchgate.net
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Robert Amsler is a retired computational lexicology, computational linguist, information scientist. His P.D. was from UT-Austin in 1980. His primary work was in the area of understanding how machine-readable dictionaries could be used to create a taxonomy of dictionary word senses (which served as the motivation for the creation of WordNet) and in understanding how lexicon can be extracted from text corpora. He also invented a new technique in citation analysis that bears his name. His work is mentioned in Wikipedia articles on Machine-Readable dictionary, Computational lexicology, Bibliographic coupling, and Text mining. He currently lives in Vienna, VA and reads email at robert.amsler at utexas. edu. He is currenly interested in chronological studies of vocabulary, esp. computer terms.
https://www.researchgate.net/profile/Robert-Amsler
Apparently follow my blog. :)
Makes me wonder how we might better process and semantically parse peoples' personal notes, particularly when they're atomic and cross-linked?
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- Oct 2022
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www.explainpaper.com www.explainpaper.com
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Another in a growing line of research tools for processing and making sense of research literature including Research Rabbit, Connected Papers, Semantic Scholar, etc.
Functionality includes the ability to highlight sections of research papers with natural language processing to explain what those sections mean. There's also a "chat" that allows you to ask questions about the paper which will attempt to return reasonable answers, which is an artificial intelligence sort of means of having an artificial "conversation with the text".
cc: @dwhly @remikalir @jeremydean
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- Aug 2022
- Dec 2021
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cacm.acm.org cacm.acm.org
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Catala, a programming language developed by Protzenko's graduate student Denis Merigoux, who is working at the National Institute for Research in Digital Science and Technology (INRIA) in Paris, France. It is not often lawyers and programmers find themselves working together, but Catala was designed to capture and execute legal algorithms and to be understood by lawyers and programmers alike in a language "that lets you follow the very specific legal train of thought," Protzenko says.
A domain-specific language for encoding legal interpretations.
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Sloman, S. A. (2021). How Do We Believe? Topics in Cognitive Science, 0(2021), 1–14. https://doi.org/10.1111/tops.12580
Tags
- memory
- knowledge
- cognitive science
- unfamiliar circumstance
- dual system of thinking
- representational scheme
- lang:en
- pattern recognition
- information processing
- human thought
- is:article
- generalizability
- sophisticated associative model
- representational language
- causal reasoning
- predictability
Annotators
URL
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- Nov 2021
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www.nature.com www.nature.com
- Jun 2021
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Jung, Y., Lee, Y. K., & Hahn, S. (2021). Web-scraping the Expression of Loneliness during COVID-19. PsyArXiv. https://doi.org/10.31234/osf.io/59gwk
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- Mar 2021
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psyarxiv.com psyarxiv.com
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Lindow, Mike, David DeFranza, Arul Mishra, and Himanshu Mishra. ‘Scared into Action: How Partisanship and Fear Are Associated with Reactions to Public Health Directives’. PsyArXiv, 12 January 2021. https://doi.org/10.31234/osf.io/8me7q.
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arxiv.org arxiv.org
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Kozlowski, Diego, Jennifer Dusdal, Jun Pang, and Andreas Zilian. ‘Semantic and Relational Spaces in Science of Science: Deep Learning Models for Article Vectorisation’. ArXiv:2011.02887 [Physics], 5 November 2020. http://arxiv.org/abs/2011.02887.
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- Aug 2020
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onlinelibrary.wiley.com onlinelibrary.wiley.com
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Bhatia, S., Walasek, L., Slovic, P., & Kunreuther, H. (2020). The More Who Die, the Less We Care: Evidence from Natural Language Analysis of Online News Articles and Social Media Posts. Risk Analysis, risa.13582. https://doi.org/10.1111/risa.13582
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psyarxiv.com psyarxiv.com
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Hull, T., Levine, J., Bantilan, N., Desai, A., & Majumder, M. S. (2020, August 13). Digital phenotyping of complex psychological responses to the COVID-19 pandemic. https://doi.org/10.31234/osf.io/qtrpf
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- Jul 2020
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osf.io osf.io
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Rosati, G., Domenech, L., Chazarreta, A., & Maguire, T. (2020). Capturing and analyzing social representations. A first application of Natural Language Processing techniques to reader’s comments in COVID-19 news. Argentina, 2020 [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/3pcdu
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- Jun 2020
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psyarxiv.com psyarxiv.com
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Meyerhoff, H. S., Brand, A.-K., & Scholl, A. (2020). In Case of Doubt for the Suspicion?: When People Falsely Remember Facts in the News as Being Uncertain. https://doi.org/10.31234/osf.io/rct7a
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- May 2020
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arxiv.org arxiv.org
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Katz, D. M., Coupette, C., Beckedorf, J., & Hartung, D. (2020). Complex Societies and the Growth of the Law. ArXiv:2005.07646 [Physics]. http://arxiv.org/abs/2005.07646
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Kennedy, B., Atari, M., Davani, A. M., Hoover, J., Omrani, A., Graham, J., & Dehghani, M. (2020, May 7). Moral Concerns are Differentially Observable in Language. https://doi.org/10.31234/osf.io/uqmty
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- Apr 2020
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en.wikipedia.org en.wikipedia.org
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arxiv.org arxiv.org
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Kerzendorf, W. E., Patat, F., Bordelon, D., van de Ven, G., & Pritchard, T. A. (2020). Distributed peer review enhanced with natural language processing and machine learning. Nature Astronomy. https://doi.org/10.1038/s41550-020-1038-y
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