Misinformation exposure and extreme right-wing ideology appear associated in this report. Others find that it is partisanship that predicts susceptibility.

This suggests the misinformation sharing elites may influence whether followers become more extreme. There is little incentive not to stoke outrage as it improves engagement.

We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation.

ReconfigBehSci [@SciBeh]. (2021, August 6). The pathologies of science Twitter are on full display in this thread featuring a non-expert blasting an epidemiologist for “stealing” an idea (a minor statistical insight) that is part of epidemiological basic understanding [Tweet]. Twitter. https://twitter.com/SciBeh/status/1423688923348299781

Explicit example of someone using a zettelkasten to develop ideas and create content for distribution online and within social media.

https://www.reddit.com/r/antinet/comments/vgtyuf/mastery_requires_theory_application_of_theory_is/

Mike Caulfield. (2021, March 10). One of the drivers of Twitter daily topics is that topics must be participatory to trend, which means one must be able to form a firm opinion on a given subject in the absence of previous knowledge. And, it turns out, this is a bit of a flaw. [Tweet]. @holden. https://twitter.com/holden/status/1369551099489779714

Virpi Flyg on Twitter. (n.d.). Twitter. Retrieved 1 April 2022, from https://twitter.com/VirpiFlyg/status/1452995562224201736

Some trucker convoy organizers have history of white nationalism, racism—National | Globalnews.ca. (n.d.). Global News. Retrieved January 31, 2022, from https://globalnews.ca/news/8543281/covid-trucker-convoy-organizers-hate/

Garland, J., Ghazi-Zahedi, K., Young, J.-G., Hébert-Dufresne, L., & Galesic, M. (2022). Impact and dynamics of hate and counter speech online. EPJ Data Science, 11(1), 1–24. https://doi.org/10.1140/epjds/s13688-021-00314-6

https://www.nytimes.com/2015/02/15/magazine/how-one-stupid-tweet-ruined-justine-saccos-life.html

Mazumdar, S., & Thakker, D. (2020). Citizen Science on Twitter: Using Data Analytics to Understand Conversations and Networks. Future Internet, 12(12), 210. https://doi.org/10.3390/fi12120210

https://www.mdpi.com/1999-5903/12/12/210

Clift, A. K., von Ende, A., Tan, P. S., Sallis, H. M., Lindson, N., Coupland, C. A. C., Munafò, M. R., Aveyard, P., Hippisley-Cox, J., & Hopewell, J. C. (2021). Smoking and COVID-19 outcomes: An observational and Mendelian randomisation study using the UK Biobank cohort. Thorax, thoraxjnl-2021-217080. https://doi.org/10.1136/thoraxjnl-2021-217080

Mattei, M., Caldarelli, G., Squartini, T., & Saracco, F. (2021). Italian Twitter semantic network during the Covid-19 epidemic. EPJ Data Science, 10(1), 1–27. https://doi.org/10.1140/epjds/s13688-021-00301-x

The Daily 202: Nearly 30 groups urge Facebook, Instagram, Twitter to take down vaccine disinformation—The Washington Post. (n.d.). Retrieved August 2, 2021, from https://www.washingtonpost.com/politics/2021/07/19/daily-202-nearly-30-groups-urge-facebook-instagram-twitter-take-down-vaccine-disinformation/?utm_source=twitter&utm_campaign=wp_main&utm_medium=social

Example of a professor/research who has apparently made his Tweets public, but intends to re-lock them majority of threat is over.

Sanders, J. G., Tosi, A., Obradovic, S., Miligi, I., & Delaney, L. (2021). Lessons from lockdown: Media discourse on the role of behavioural science in the UK COVID-19 response. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.647348

Nathan Young. (2021, February 3). Can we gather all covid tweets from large UK accounts, anonymise them put them on a website, let the public score them true to false then rank the accounts? [Tweet]. @NathanpmYoung. https://twitter.com/NathanpmYoung/status/1356928462565564416

Gallotti, R., Valle, F., Castaldo, N., Sacco, P., & De Domenico, M. (2020). Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics. Nature Human Behaviour, 4(12), 1285–1293. https://doi.org/10.1038/s41562-020-00994-6

Chang, H.-C. H., Chen, E., Zhang, M., Muric, G., & Ferrara, E. (2021). Social Bots and Social Media Manipulation in 2020: The Year in Review. ArXiv:2102.08436 [Cs]. http://arxiv.org/abs/2102.08436

Jose-Luis Jimenez. (2021, February 5). 1/ Some reflections on scientific Twitter sociology I hadn’t used Twitter much before the pandemic. I was used to the politics of peer-review, grants, large studies etc. But scientific Twitter can be the Wild West by comparison. [Tweet]. @jljcolorado. https://twitter.com/jljcolorado/status/1357737374621515776

Darren Dahly. (2021, February 24). @SciBeh One thought is that we generally don’t ‘press’ strangers or even colleagues in face to face conversations, and when we do, it’s usually perceived as pretty aggressive. Not sure why anyone would expect it to work better on twitter. Https://t.co/r94i22mP9Q [Tweet]. @statsepi. https://twitter.com/statsepi/status/1364482411803906048

Ryan McNamara 🧬 on Twitter. (n.d.). Twitter. Retrieved 19 February 2021, from https://twitter.com/Ryan_Mac_Phd/status/1361435791004758018

Broniatowski, D. A., Jamison, A. M., Qi, S., AlKulaib, L., Chen, T., Benton, A., Quinn, S. C., & Dredze, M. (2018). Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate. American Journal of Public Health, 108(10), 1378–1384. https://doi.org/10.2105/AJPH.2018.304567

You cannot practice public health without engaging in politics. (2021, March 29). The BMJ. https://blogs.bmj.com/bmj/2021/03/29/you-cannot-practice-public-health-without-engaging-in-politics/

Aletti, G., Crimaldi, I., & Saracco, F. (2020). A model for the Twitter sentiment curve. ArXiv:2011.05933 [Physics]. http://arxiv.org/abs/2011.05933

New tool for the early detection of public health threats from Twitter data: Epitweetr. (2020, October 1). European Centre for Disease Prevention and Control. https://www.ecdc.europa.eu/en/news-events/new-tool-early-detection-public-health-threats-twitter-data-epitweetr

ReconfigBehSci on Twitter: “having spent a few days looking at ‘debate’ about COVID policy on lay twitter (not the conspiracy stuff, just the ‘we should all be Sweden’ discussions), the single most jarring (and worrying) thing I noticed is that posters seem completely undeterred by self contradiction 1/3” / Twitter. (n.d.). Retrieved September 23, 2020, from https://twitter.com/SciBeh/status/1308340430170456064

Haman, M. (2020). The use of Twitter by state leaders and its impact on the public during the COVID-19 pandemic. https://doi.org/10.31235/osf.io/u4maf

Gallotti, R., Valle, F., Castaldo, N., Sacco, P., & De Domenico, M. (2020). Assessing the risks of “infodemics” in response to COVID-19 epidemics. ArXiv:2004.03997 [Physics]. http://arxiv.org/abs/2004.03997

Viglione, G. (2020). Has Twitter just had its saddest fortnight ever? Nature. https://doi.org/10.1038/d41586-020-01818-3

Gencoglu, O., & Gruber, M. (2020). Causal Modeling of Twitter Activity During COVID-19. ArXiv:2005.07952 [Cs]. http://arxiv.org/abs/2005.07952

Samuel, J.; Ali, G.G.M.N.; Rahman, M.M.; Esawi, E.; Samuel, Y. COVID-19 Public Sentiment Insights and Machine Learning for Tweets Classification. Preprints 2020, 2020050015 (doi: 10.20944/preprints202005.0015.v1)

Battiston, P., Kashyap, R., & Rotondi, V. (2020, May 11). Trust in science and experts during the COVID-19 outbreak in Italy. https://doi.org/10.31235/osf.io/5tch8

This quote comes from a larger piece by Robin Sloan. (I don't know who that is though)

The problem with social media is that the equivalent to working with the garage door open (working in public) is repeatedly talking in public about what you're doing.

One problem with this is that you need to choose what you want to talk about, and say it. This emphasizes whatever you select, not what would catch a passerby's eye.

The other problem is that you become more visible by the more you talk. Conversely, when you stop talking, you become invisible.

Unfortunately, this is very true. We can say the same about fake news. Such practices can contribute to hurting the validity of the overall data. The Twitter data is not collected with systematic investigation or systematic collection methods. This data collection method heavily relies on “public opinion”. I do think that if one wants to find general public sentiment or general public opinion, this is a great way to do it.

is being in the public the problem, or is it the change of the tone or format of discourse?

fully public honest but still civil discussions aiming at making a case, creating more awareness, finding solutions, or trying to understand, clarify, show genuine interest .... is better than a public fight .. right? or am I misunderstanding this?