This isn't a great article IMO (I say as someone who is a big fan of qualitative user research, mixed methods, etc).
Per the first example, many types of attitudinal data can be quantified and conflating attitudinal data with qualitative data is itself a fallacy. It's possible that there were quantitative attitudinal signals that could have been captured or created as inputs to a more accurate model.
Per the second example, this is more a question of data validity than the metric itself. If the metric could be validated through better design and gamification prevented then it would likely still be a helpful indicator. Granted this is a very hard problem.
That's a good point, you don't always know, so your quantitative data starts with qualitative (you decide what to measure).
But, for the common cases you can follow the industry standard measurements. They also learned from the war question mentioned in the article, now they just measure public support, too.
Per the first example, many types of attitudinal data can be quantified and conflating attitudinal data with qualitative data is itself a fallacy. It's possible that there were quantitative attitudinal signals that could have been captured or created as inputs to a more accurate model.
Per the second example, this is more a question of data validity than the metric itself. If the metric could be validated through better design and gamification prevented then it would likely still be a helpful indicator. Granted this is a very hard problem.