- May 2022
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www.thecut.com www.thecut.com
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Matt Taibbi asked his subscribers in April. Since they were “now functionally my editor,” he was seeking their advice on potential reporting projects. One suggestion — that he write about Ibram X. Kendi and Robin DiAngelo — swiftly gave way to a long debate among readers over whether race was biological.
There's something here that's akin to the idea of bikeshedding? Online communities flock to the low lying ideas upon which they can proffer an opinion and play at the idea of debate. If they really cared, wouldn't they instead delve into the research and topics themselves? Do they really want Taibbi's specific take? Do they want or need his opinion on the topic? What do they really want?
Compare and cross reference this with the ideas presented by Ibram X. Kendi's article There Is No Debate Over Critical Race Theory.
Are people looking for the social equivalent of a simple "system one" conversation or are they ready, willing, and able to delve into a "system two" presentation?
Compare this also with the modern day version of the Sunday morning news (analysis) shows? They would seem to be interested in substantive policy and debate, but they also require a lot of prior context to participate. In essence, most speakers don't actually engage, but spew out talking points instead and rely on gut reactions and fear, uncertainty and doubt to make their presentations. What happened to the actual discourse? Has there been a shift in how these shows work and present since the rise of the Hard Copy sensationalist presentation? Is the competition for eyeballs weakening these analysis shows?
How might this all relate to low level mansplaining as well? What are men really trying to communicate in demonstrating this behavior? What do they gain in the long run? What is the evolutionary benefit?
All these topics seem related somehow within the spectrum of communication and what people look for and choose in what and how they consume content.
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- Mar 2022
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infodemiology.jmir.org infodemiology.jmir.org
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Quinn, E. K., Fenton, S., Ford-Sahibzada, C. A., Harper, A., Marcon, A. R., Caulfield, T., Fazel, S. S., & Peters, C. E. (2022). COVID-19 and Vitamin D Misinformation on YouTube: Content Analysis. JMIR Infodemiology, 2(1), e32452. https://doi.org/10.2196/32452
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- Jan 2022
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Fischer, O., Jeitziner, L., & Wulff, D. U. (2021). Affect in science communication: A data-driven analysis of TED talks. PsyArXiv. https://doi.org/10.31234/osf.io/28yc5
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- Nov 2021
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Nelson (2020) - Computational Grounded Theory: A Methodological Framework
- urn:x-pdf:9f22952783af4581a3525c1a1497328a
- https://is.gd/k2YLcm
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www.diva-portal.org www.diva-portal.org
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Qualitative content analysis
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- Sep 2021
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www.tandfonline.com www.tandfonline.com
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Moran, M. B., Lucas, M., Everhart, K., Morgan, A., & Prickett, E. (2016). What makes anti-vaccine websites persuasive? A content analysis of techniques used by anti-vaccine websites to engender anti-vaccine sentiment. Journal of Communication in Healthcare, 9(3), 151–163. https://doi.org/10.1080/17538068.2016.1235531
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- Apr 2021
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arxiv.org arxiv.org
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Yang, K.-C., Pierri, F., Hui, P.-M., Axelrod, D., Torres-Lugo, C., Bryden, J., & Menczer, F. (2020). The COVID-19 Infodemic: Twitter versus Facebook. ArXiv:2012.09353 [Cs]. http://arxiv.org/abs/2012.09353
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- Mar 2021
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twitter.com twitter.com
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Darren Dahly. (2019, September 4). It seems appropriate to do a thread on our recent session about the use of Twitter by statisticians. Https://t.co/eFwLDuXnOU [Tweet]. @statsepi. https://twitter.com/statsepi/status/1169313702715281408
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- Aug 2020
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www.tandfonline.com www.tandfonline.com
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Arqoub, O. A., Elega, A. A., Özad, B. E., Dwikat, H., & Oloyede, F. A. (2020). Mapping the Scholarship of Fake News Research: A Systematic Review. Journalism Practice, 0(0), 1–31. https://doi.org/10.1080/17512786.2020.1805791
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- Jul 2020
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osf.io osf.io
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Motta, M., Stecula, D., & Farhart, C. E. (2020). How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a8r3p
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osf.io osf.io
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Weed, M. (2020). Models and methods to analyse the interaction of evidence and policy in the first 100 days of the UK government’s response to COVID-19 (v1.1). https://doi.org/10.31235/osf.io/f73u4
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- Jun 2020
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www.annualreviews.org www.annualreviews.org
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Chong, D., & Druckman, J. N. (2007). Framing Theory. Annual Review of Political Science, 10(1), 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054
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arxiv.org arxiv.org
- Jan 2020
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diposit.ub.edu diposit.ub.edu
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) +)
Krippendorff, aquí en la bibliografía: Content analysis. An introduction to its methodology.
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- Oct 2017
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rampages.us rampages.us
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applying networkand content analyses
I came across this article while doing research for last week’s blog. I know this is not a straight forward SNA article, but I found it very interesting since it is a combination of SNA and content analysis. Considering this week’s readings on different data collection method, I found their approach of collecting data from Twitter very unique. In this context, content analysis refers to analyzing tweets and their content. Recently, content analysis is being used in various fields. Even social researchers are taking this opportunity of exploring already existing data. Do you think you can use the combination of both SNA and content analysis in your own research field?
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- Jun 2016
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voyant-tools.org voyant-tools.org
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Voyant Tools is a web-based reading and analysis environment for digital texts.
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