Nutpicking
An argumentum ad hominem is a rhetorical approach that attacks an opposing party's character, beliefs, motives, or similar attributes to implicitly undermine their arguments without directly addressing the arguments themselves.
A simple example of ad hominem (as it is often shorthanded) would be countering the statement, "Capitalism is the best method for fairly distributing scarce resources" by saying, "You would say that, coming from a wealthy family."
In this case, rather than addressing the proposition at hand, an attack on the person making the proposition is leveraged—the idea being to undercut the proposer's credibility by implying they're wealthy beneficiaries of the system they're defending, and thus would obviously defend it (in turn implying a lack of credibility for the proposer and the system they're defending).
Cherry-picking is another fallacy that involves finding and utilizing data that supports one's own argument, despite that data not being representative of the larger body of available data.
If I don't believe that climate change is influencing weather patterns, making things warmer, on average, over time, I might scrounge up temperature figures that show colder weather in some areas in a given year, which would seem to indicate that warming trends aren’t universal, and thus, folks worried about climate change are upset about nothing.
That flicker of lower temperatures, however, might be a blip in a larger trend that shows—over the course of decades or centuries—average temperatures are indeed ticking higher.
It's almost always possible, then, for a properly motivated person to cherry-pick a snippet of data that in isolation seems to say one thing, but which in a larger, more complete context shows another.
Nutpicking is a variation of cherry picking that involves finding folks on the opposite side of a debate who hold extreme versions of the opposing argument and positioning them as the true representatives of that group (and the group's arguments).
If you're arguing against stricter immigration laws, for instance, you might "nutpick" anti-immigration politicians who are real-deal racists, and suggest that everyone who shares their views on immigration are also racists.
You might also argue that because some Democrats (in US politics) hold hardline socialist views that the Democratic Party is a socialist party.
In both cases, this approach paints an entire group of people with a broad brush that doesn't line up with actual behaviors or beliefs. But it can be easier to win people to your side if it seems like the other side is full of radicals with ideas that defy the mainstream.
If it's a question of supporting pro-immigration policies or siding with hardcore racists, many people will opt for the former, even if they're not especially pro-immigration. And if a debate is framed as being between hardline socialists and not-hardline socialists, many people will vote for the latter, even if they might actually agree with the majority of the Democratic Party platform, and disagree with the majority of what the Republicans are saying that election cycle.
Modern debate—empowered by social media and other mass-broadcasting communication technologies and systems—is supersaturated with nutpicking to the point that it's nearly impossible to avoid.
It's sometimes possible to filter nutpicked claims by paying attention to opinion polls and surveys (which also have issues) about the beliefs of people in various groups, rather than what politicians and other biased sources say.
It's also worth remembering that just as straw man arguments (the misrepresentation of an opposing party's ideas, usually so they're easier to knock down) are less useful than steel man arguments (the strongest-possible version of an opposing party's argument) in the long-term, so too is a struggle against nutpicked representatives of an opposing idea generally less ultimately useful than legitimate arguments against the same (though folks with only short-term gains in mind will tend to get more mileage from nutpicking and straw men).
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