- Nov 2024
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Local file Local fileLayout 11
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In the 1950s and 1960s, information retrieval (IR) theorists drew a distinction between“document retrieval systems” and “fact retrieval systems.” The former, were intendedto retrieve, in response to a user’s query, all documents that might contain informationpertinent to answering that query, while the latter were to lead the user directly tospecific pieces of information – facts – embedded within the documents being searchedthat would answer his or her question. The idea of information analysis clearlyprovided the theoretical impetus for fact retrieval (aka question-answering) systems
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- Oct 2022
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Local file Local file
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here are several ways I havefound useful to invite the sociological imagination:
C. Wright Mills delineates a rough definition of "sociological imagination" which could be thought of as a framework within tools for thought: 1. Combinatorial creativity<br /> 2. Diffuse thinking, flâneur<br /> 3. Changing perspective (how would x see this?) Writing dialogues is a useful method to accomplish this. (He doesn't state it, but acting as a devil's advocate is a useful technique here as well.)<br /> 4. Collecting and lay out all the multiple viewpoints and arguments on a topic. (This might presume the method of devil's advocate I mentioned above 😀)<br /> 5. Play and exploration with words and terms<br /> 6. Watching levels of generality and breaking things down into smaller constituent parts or building blocks. (This also might benefit of abstracting ideas from one space to another.)<br /> 7. Categorization or casting ideas into types 8. Cross-tabulating and creation of charts, tables, and diagrams or other visualizations 9. Comparative cases and examples - finding examples of an idea in other contexts and time settings for comparison and contrast 10. Extreme types and opposites (or polar types) - coming up with the most extreme examples of comparative cases or opposites of one's idea. (cross reference: Compass Points https://hypothes.is/a/Di4hzvftEeyY9EOsxaOg7w and thinking routines). This includes creating dimensions of study on an object - what axes define it? What indices can one find data or statistics on? 11. Create historical depth - examples may be limited in number, so what might exist in the historical record to provide depth.
Tags
- dialogues
- generalization
- dimensions
- historical context
- abstraction
- thinking routines
- categorization
- terms
- flâneur
- sociological imagination
- combinatorial creativity
- definitions
- compass points
- building blocks
- trend analysis
- The Sociological Imagination
- browsing
- information visualization
- diffuse thinking
- opposites
- historical perspective
- taxonomies
- devil's advocate
Annotators
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- Dec 2021
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www.npr.org www.npr.org
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Wood, D., & Brumfiel, G. (2021, December 5). Pro-Trump counties now have far higher COVID death rates. Misinformation is to blame. NPR. https://www.npr.org/sections/health-shots/2021/12/05/1059828993/data-vaccine-misinformation-trump-counties-covid-death-rate
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- Feb 2021
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psyarxiv.com psyarxiv.com
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Lakens, D. (2021). Sample Size Justification. PsyArXiv. https://doi.org/10.31234/osf.io/9d3yf
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- Oct 2020
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oro.open.ac.uk oro.open.ac.uk
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Burel, Gregoire; Farrell, Tracie; Mensio, Martino; Khare, Prashant and Alani, Harith (2020). Co-Spread of Misinformation and Fact-Checking Content during the Covid-19 Pandemic. In: Proceedings of the 12th International Social Informatics Conference (SocInfo), LNCS.
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- Sep 2020
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psyarxiv.com psyarxiv.com
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Karwowski, M., Zielinska, A., Jankowska, D., Strutynska, E., Omelanczuk, I., & Lebuda, I. (2020). Creative Lockdown? A Daily Diary Study of Creative Activity During Pandemics. 10.31234/osf.io/kvesm
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- Jul 2020
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Gleeson, J. P., Onaga, T., Fennell, P., Cotter, J., Burke, R., & O’Sullivan, D. J. P. (2020). Branching process descriptions of information cascades on Twitter. ArXiv:2007.08916 [Physics]. http://arxiv.org/abs/2007.08916
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- May 2020
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leoferres.info leoferres.info
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Ferres, L. (2020 April 10). COVID19 mobility reports. Leo's Blog. https://leoferres.info/blog/2020/04/10/covid19-mobility-reports/
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epjdatascience.springeropen.com epjdatascience.springeropen.com
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Vilella, S., Paolotti, D., Ruffo, G. et al. News and the city: understanding online press consumption patterns through mobile data. EPJ Data Sci. 9, 10 (2020). https://doi.org/10.1140/epjds/s13688-020-00228-9
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- Apr 2020
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Wang, T., Chen, X., Zhang, Q., & Jin, X. (2020, April 26). Use of Internet data to track Chinese behavior and interest in COVID-19. https://doi.org/10.31234/osf.io/j6m8q
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Source: Office for National Statistics - United Kingdom
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Punn, N. S., Sonbhadra, S. K., & Agarwal, S. (2020). COVID-19 Epidemic Analysis using Machine Learning and Deep Learning Algorithms [Preprint]. Health Informatics. https://doi.org/10.1101/2020.04.08.20057679
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arxiv.org arxiv.org
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Alam, F., Sajjad, H., Imran, M., & Ofli, F. (2020). Standardizing and Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing. ArXiv:2004.06774 [Cs]. http://arxiv.org/abs/2004.06774
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