Social media not only provides marketers with a means of communicating with their customers, but also a way to better understand their customers. Viewing consumers’ social media activity as the “voice of the consumer,” this session exposes learners to the analytic methods that can be used to convert social media data to marketing insights. In Introduction to Social Media Analytics, learners will be exposed to both the benefits and limitations of relying on social media data compared to traditional methods of marketing research. Partnering with a leading social media listening platform, this course provides learners with the foundational skills of social media listening including the creation of monitors and common social media metrics. Moving beyond social media listening, this course shows learners how social media data can be used to provide insights into market structure and consumers’ perceptions of the brand. Learners will have the opportunity to assess data and discern how to "listen" to the data by watching video lectures and completing activities, practice quizzes, discussion boards, and peer assessments.
Opinion Science and Dynamics - Part 2
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From the course by Emory University
Introduction to Social Media Analytics
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From the lesson
Opinion Science and Dynamics
This module will discuss how to evaluate and judge social media contributions. You will be able to better determine what data is useful or not.
Meet the Instructors
David SchweidelAssociate Professor of Marketing
Goizueta Business School
So let’s take a moment and pause, and just think about your own behavior.
Think about when was the last time that you posted a review?
Whether it's a review or social media content mentioning a particular brand,
when was the last time that you did it and
what motivated you to engage in that particular behavior?
Now, there's been a lot of research and this predates kind of the social
media era, there's a lot of research into word of mouth within marketing and
why do people engage in word of mouth activity.
And two of the goals that have been identified when it comes to social media
use, have to be do with an affiliation goal.
That is I want to be seen as part of a group, and with a persuasion goal.
My objective here is to change your mind.
My objective here is to have an impact on your decision making.
Now, those are two sets of reasons why we might see people
engage in posting content online.
More broadly, some of the motivations that have been identified in offline contexts,
self-enhancement, being an objective of drawing attention to oneself.
We've also seen a product involvement, that people are very invested in
a particular product, wanting to talk about that product.
Altruism being another motivation where the goal is I want to help other people,
and that altruism could take different forms.
That could take on the form of positive word of mouth, saying, this product
is great and I want to tell other people about how this product helped me.
It could also take on a negative form on this product is bad, it let me down.
I don't want other people to make the same mistake that I made, right?
Now, when we look at the motives that have been identified in online research,
we can start to see a lot of these tend to overlap each other, right?
So concern for others could be seen as a form of altruism.
If I'm trying to get customer service,
you could think of that as being involved with the product.
Assisting the company, I love this company, but
this product has a minor problem that they should fix.
So that could be seen as a form of altruism, helping out the company.
Perhaps I'm trying to get advice, I'm trying to gain some help,.
Venting, saying negative feelings, just blowing off steam.
In some sense, perhaps that's altruistic.
I had a horrible experience,
others shouldn't go through the same thing that I went through.
One of the newer ones that we're seeing though is an economic motivation.
A lot of organizations, a lot of businesses in particular,
encouraging people to post content online, whether it's running sweepstakes or
restaurants offering you a free appetizer, free drinks, for posting comments online.
Because consumers turn to Yelp, Amazon, they turn to user-generated
content to get information about where they should be conducting their business.
So businesses have an incentive to encourage that activity.
All right, and so this is a framework that we've put together in some of
the work we did to understand why people are posting content online.
And the big distinction that I want to draw here is between the opinion formation
stage, which is the upper part of this box, and
then the opinion expression stage, which is the lower part of this box.
We're not the first ones to put forth this idea, the distinctions between opinion
formation and opinion expression have been talked about extensively, in the public
opinion research, in the political science literature.
But the difference is a simple one, but I think an important one.
Whenever we buy a product, we experience that product.
We reconcile what we expected with our experience of the product
and we talk about that as the post-purchase evaluation.
Well, just because I've formed that opinion internally,
doesn't mean that I care enough to express that opinion.
That's concerned with the opinion expression stage.
So my post purchase evaluation is going to drive my decision to post yes or no.
It's also going to drive what I post.
In this case, is it going to be positive?
Is it going to be negative?
Now, my internal opinion
isn't the only thing that's going to drive the opinion that I choose to express.
The opinion that I choose to express is also going to be driven
by what other people have said previously.
And so there might be a selection effect where previously posted ratings
affect my decision to even participate in the conversation.
Maybe I have an opinion that I'd like to share, but everyone else has said what I
would say, and I have nothing new to add to the conversation, so
I decide that I'm not going to participate.
Or perhaps, there's too much dissention in the previous comments,
and I don't want to deal with any conflict, so I decide not to participate.
All right, so that would be the selection effect.
The adjustment effect that we're concerned with is that previous ratings may lead me
to actually alter the opinion that I hold in terms of when I choose to express it.
So I might think that the product was the best thing ever, but
other people are negative about it.
All right, well, maybe that's going to cause me to temper my enthusiasm for
it a little bit.
I might go the other way, though.
Maybe I have a negative opinion and other people are also negative.
And I say, well, maybe it wasn't as bad as I really thought it was,
so maybe I'm going to boost it up a little bit.
This has been documented in terms of bandwagon effects.
It's actually one of the reasons why the results of elections on
the East Coast don't get reported until after polls close on
the West Coast in the United States because we don't want the earlier
decisions that people have made to affect later decisions.
And so one of the reasons why we run into potential problems
looking at user generated content as a gauge for
how much people like a product potentially is who
are the people who are ultimately contributing the comment?
Most of who we see, it's going to people who have a strong opinion.
If you really like the product, you're more prone to contribute a comment.
If you really dislike the product, you're probably going to say something about it.
But everyone who's kind of got that moderate opinion,
they're somewhere in the middle, they might lean toward liking it but it's not
a strong enough motivation for them to go online and say something about it.
Those people in the middle are actually less likely to express an opinion online.
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