#18 - An analysis of the language in social media messages

[Administrator]

Please post your questions below!

[jwheeler]

This one was confusing to me. I chose C, thinking that if people are posting positive messages on social media in the morning, but talking using negative language while at work that a.m., then it would undermine the conclusion that people have a good mood, worse, mood, then better mood over the course of a day.

I kind of see why E could be right (I think) if it's saying that you have different people posting in morning & night, so that doesn't reflect a comparison of the mood of the same person. You're merely seeing the mood of 1 person in the morning vs 1 person at night; hardly a strong basis for comparison. Is it saying that since you're not comparing apples to apples, then you can't make that argument?

[Moris_cn]

I chose C thinking that the conclusion in the stimulus is making a general claim about a person's mood. If words used in other forms of communication indicate otherwise, that conclusion would be undermined. Does this reasoning make sense?

[Adam Tyson]

Hey guys, thanks for the questions! The issue in this stimulus is that the author is using data about words used at different times of the day in social media to draw conclusions about the changing moods of the people using those words. That is, evidence collected from a group (users of social media) is being used to draw conclusions about the members of that group ("a person's mood"). This looks like a Whole-to-Part Flaw, also known as an Error of Division. The author must have assumed that the changes in the cumulative tone of the messages over the course of the day are attributable to changes in the moods of the individuals posting the messages, but they could instead be due to changes in which people are posting those messages.

Answer C brings up an issue that might, with more information, weaken the argument. What if we looked at, say, email messages sent throughout the day by a group of people, and found that those messages used negative words early, then gradually got more positive throughout the day, and then turned negative again in the late evening? If that happened, that might weaken the original claim, but failing to consider that isn't really a flaw in the original argument. The author doesn't have to consider every possible source of evidence in order for his argument to be valid, so failing to consider some other evidence is not, by itself, a flaw. Rather, the flaw is in failing to consider that the evidence that he DID use may not indicate what he assumed it did.

Put another way, the flaw in pretty much any bad argument is in the author making an unwarranted assumption of some sort. This author's big bad assumption was that the group trend indicated individual trends. He assumed nothing about how those words were used in other forms of communication, but only what their use in social media tells us about the people sending the messages.

[lmasta0340]

I understand why E is the correct answer choice, but I am having some trouble eliminating answer choice B. If many people use words on social media that are not associated with mood, then it seems like this would be an unrepresentative sample size. Given that "many" really means "some," would this answer choice be correct if, instead of "many," the author said "most?"

Thank you in advance!

[Christen Hammock]

Hey lmasta!

There's no sample size problem in the stimulus, so Answer Choice (B) can't be right! Just because people use non-"mood" words online doesn't mean that we can't target the "mood" words to tell us something. You'd be right if, for example, the stimulus indicated that the researchers only examined words that indicated a positive mood and ignored words that indicated a negative mood.

In general, targeting a particular group or characteristic isn't reflective of a sample size problem. For example, if we take a sample size of1,000 college students out of all the college students in the United States, that's okay! It doesn't matter that there are billions of non-college students who live in the world. If we're studying college students, it's okay to pick only from that group. Similarly, if we're studying how mood gets expressed on social media, it's okay to just focus on "mood" words.

[amys45]

Hello PowerScore!

I was hoping to get some help on why answer choice "D" is correct. This is what I've come-up with so far:

The argument concludes that people are happy in the morning, less happy the afternoon, and then become happier again in the evening. Answer choice "B" says that the argument ignores the possibility that there are significantly more posts in the morning compared to the evening. However, if this were the case, this doesn't actually weaken the argument since the stimulus tells us that the average number of words associated with positive moods increases sharply throughout the evening. So, this would actually lend more support to this part of the argument, since there are less posts yet more words associated with positive moods.

If my reasoning here is correct, though, would it then be the case that if this answer choice had said that there are more posts during the morning and evening compared to the afternoon, that this may weaken the argument?

Thank you!

[Adam Tyson]

I don't think the number of messages at different times of day would matter, amys45, because the stimulus tells us that the analysis looked at the average. The issue isn't how many words of different types are used (a numbers idea), but how common those words are at different times (a percentages idea). There could be more messages in the evening, or fewer, but the issue is still how common the positive mood words are within whatever number of messages were analyzed.