Data interpretation and use of language
Mathematics, especially statistics, wasn't exactly my favourite subject at school. But in the world of PR & social media, you simply can't do without basic mathematical knowledge.
I am very interested in the issue of fake news. I find it exciting how fake news can be used in election campaigns. For example, I'm reading the book "The Persuaders: Winning Hearts and Minds in a Divided Age" and "Changing the Narrative - Information Campaigns, Strategy and Crisis Escalation in the Digital Age". What both books have in common is that they are based on research. These also need to be critically evaluated, e.g. their data base or things that are not conclusively correlated.
This article here "Increasing accuracy motivations using moral reframing does not reduce Republicans' belief in false news" challenged me a bit. Not because of what it says, but because I simply need to get better at statistics. With a little time and common sense, I was able to crack this nut. And I would like to take this opportunity to recommend the following article.
Statistically significant
The article "5 things journalists need to know about statistical significance" describes very clearly what needs to be considered when interpreting data and statistics. Wrong conclusions drawn from statistics and surveys are the basis of fake news. Of course, it is tempting to cram dramatic correlations into a headline. That generates clicks. But that is deceiving the reader, and that is fake news. We were served this kind of fake news very often in COVID times. So please read this article. I'm going to get out my maths books again and study statistics.
5 things journalists should know about significance
The article provides important insights into the concept of statistical significance and its role in research. The author emphasises that statistical significance does not necessarily mean practical significance and warns against the misuse of "p-values", a common measure of statistical significance.
The article also emphasises the importance of "effect size". This measures the magnitude of a phenomenon and the role of confidence intervals, which indicate a range of plausible values for an unknown parameter.
Euphemism and hyperbole are both dangers for language
The misuse of language, especially euphemisms and hyperbole, has a direct impact on communication and understanding. Euphemisms are a problem, but exaggeration in social networks is even worse. The result is inflammatory language to attract attention. Milder terms are replaced by increasingly extreme ones, e.g. "prejudiced" by "racist" and then by "white supremacy". The author argues that this misuse of language, particularly the excessive use of extreme terms, makes it difficult to accurately describe real atrocities.