This chapter is about writing about trends and explaining them, and it is loaded with info. This blog looks a little more like notes than a blog. Old habits die hard.
I liked reading the example piece about social media in college admissions, and the side notes are helpful (sometimes obvious, but it’s nice to see each element pointed out). I found it interesting that the author originally had another topic in mind but changed direction.
Tips from the chapter:
- proof the trend exists then explain the trend
- Establish ethos: understand your audience–know what they do and do not know, and whether or not it is a controversial matter
- present yourself as an authority–use precise data, interviews, consult sources, quote exports
- objective voice–no first person! no opinion and attribution
Choosing a good topic: make observations and convert them to analysis
This, I think, is the hardest part: finding a topic that will work for the assignment and that will be interesting (to readers and the author). I like the texting example because it is such a major trend but I feel like the ways in which it has changed communication are pretty much common knowledge so I’m not sure what additional insight a causal analysis could provide. This is why you should test your topic: is it isolated or other examples? Are there larger implications? Are there noteworthy increases/decreases? What are the significant cause or effects?
The Analytical Thesis: define the trend and present a theory about it–signals what your readers will understand by reading your analysis
Keep track of research: books, social media, internet search engines and directories, internet databases, interviews and check for authority, currency, bias
I found the advice about “showing the human side of data” intriguing because when I think data, I don’t really think “personal”. But for someone to be included in a data figure, they must have had a personal experience with the trend. I like the idea of using the story within the data rather than simply a large impersonal numerical figure.
Using logic: avoid jumping to conclusions!
- post hoc fallacy–that something that happens is a cause of what comes after it
- correlation does not prove causation
So, if I fall asleep after this, it does not necessarily mean it was because this chapter was boring. Assuming so would be falling prey to the post hoc fallacy.
Revision: big idea reminders, restatements of previous topics, single word transitions
“Race Remixed Black? White? Asian? More Young Americans Choose All of the Above” and the other readings tie all the elements of the chapter together. They present trends and explain them using personal stories and relevant statistics.
Com 201 