Shaila Miranda discusses Social Analytics: Network and Text Methods with NodeXL and R

Summary: Miranda discusses the value of data analytics for businesses and students, especially social analytics. She shares pedagogical tools to engage students. Her book helps students overcome challenges such as fear of technology. Students discover business insights from unstructured data, including social media and other digital media. This video also includes behind-the-scenes stories about the development of the book and ends with a positive message about being a woman in Information Systems. 

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Transcript: Shaila Miranda on Social Analytics

Everything that we do in business these days is evidence-driven. We are constantly refining our decision models based on the latest evidence on hand. From recruiting new employees, to managing within the organization, to managing brands, portfolios, hospitals, everything is evidence-driven these days. So analytics is just a really important skill to get students involved with.

In fact, we are pushing our analytics curriculum down into the undergraduate program because we think even our undergraduate students to some extent should be exposed to analytics.

Social analytics. So, what sells this course to students usually is the social media data. But I think its much more about truly unstructured data. There is rich information in text, and if we are not analyzing that, if we are only analyzing things that have already been quantified, we are losing a lot of insights available to companies. More than social media, it is that type of unstructured data it is really important for students to be exposed to. 

If brands are to be aware and proactive about their management, then definitely you need to be not just social media savvy, but digital media savvy. Websites, any kind of digital location. 

How do you engage students?

The best way to get them hooked really is to have them work with data. Oftentimes telling people about topic modeling sounds very intimidating. But you get them doing topic modeling and it's like "oh, that's what I did?" and it doesn't seem like that big a deal because you had them work through it and then they are more focused on the insights instead of worrying "well maybe I couldn't have done this." 

I'm very much into experience. Through experience you learn what you are capable of, and you also discover what the data can tell you. 

Typically what I will do is have them organize into teams. So I'll have a team of three with one data set and another team of three with a related data set. Then individually they'll analyze those data sets, compare outputs and insights within the smaller group of three, put it together with the full group. 

So for example I had one group look at Twitter data on Bitcoin, and another group of three look at Twitter data on blockchain. So they look at related topics and how those come together. 

What are some of the major student challenges?

Some are really intimidated by technology. That was also the objective of saying let's go with something familiar, like Excel. You know, NodeXL is just sort-of an overlay on that familiar tool. Then we'll go to R, which seems more intimidating to people because if you haven't used R there's really no getting off the floor with it. 

But then when we get to R, I give them code. Let's run it against a data set that I give you. The code matches the data set, and then you look at the results. Then let's swap out the data set so you have to change a few of the variable names, or you have to make a few tweaks in the code. So it is incremental learning. Similar code, different data sets, then let's tweak it a little bit more. Let's do something a little bit different, maybe combine that with something you've done before. I give them something that works right off the bat to minimize the frustration that would otherwise be there. 

The other thing I wanted to do with my life was be a musician. I started playing violin. My daughter plays violin. We both learned the Suzuki method. It's the one where you start when you are really little, you have all the songs. Yeah, so you start with music you actually want to play because who wants to play scales?! So Suzuki kids start by playing songs that they hear, they sing. It's the same philosophy.

I give them the code to solve a big problem, and then they're hooked, right? This is not "Hello World,"  which which MBA or Master's students wants to write code for, but if I give them the code to actually analyze a twitter or Facebook data set, this is a sizable problem. Then we work through how we get the nuances if we change the data set, kind-of like if we change the key. I know the song, now I can do the transposition and it's not that hard. 

Tell me about an unusual student insight. 

This one student somehow got data on ship logs from the 17th and 18th century. He analyzed trade routes based on those ship logs, so he has this amazing social network based on the movement of trading ships for that time period. He looked at the networks of ports visited at different times of the year and came up with insights about how weather changed trading routes over seasons.

In Search of Meaning...

[Abby] The header on your website, "In Search of Meaning..." Tell me more about how this relates to your work!

[Shaila] Ultimately, analyzing social space, analyzing what people are talking about, is about trying to make sense of how people see the world, what they find meaningful. That cover picture for example, that tells us what different topics people are talking about related to the #wheresrey merchandise. So looking at the book, there are five different groupings, so very quickly I get a sense of the five major topics, the ideas that people are putting together. 

How did you hear about the #wheresrey example?

I have a now fifteen-year-old, who was probably 10 or eleven back then, and we were into Star Wars, and this was the first female character, so holiday time, looking for the obligatory gifts, this was really an opportunity. Then I started to notice really in mass media first, with some lag. It started showing up in social media only around December. But as far back as October, parents were saying, "hey, where's all this merchandise? You have this neat character, showcasing a strong female role in the Star Wars series for the first time, how come merchandise isn't available?" And it was months before the various companies involved started to respond to that.

There was a nine-year-old who wrote a letter saying, "Hey, I want to be able to play with these toys! How come you aren't making them available?"  And then one of the representatives of the company wrote  back, and then we started to see this moving out onto the shelves. This was two months of delay before they  even entered the conversation. We wouldn't see that now. I think companies are much more responsive to what's happening on social media. But that was like, huh, how could they have missed this for so long?

How has being a woman impacted your career? 

I think I've been very lucky. Right out of my PhD program I had a few offers and I heard that Carol Saunders, she wasn't yet faculty at Florida Atlantic University, but she was going to be department chair. When I heard that I said "Okay, I accept." So I ended up going there, and I owe her a lot. You have a strong woman role model, mentor, it's not just that it opens opportunities, but it gives you a view of what life can be like that you don't necessarily have without someone like that to model. 

Here too we have a strong group in terms of females. So right now we have Radhika [Santhanam], very strong female character, Teresa Shaft, and Alex Durcikova, two more very strong women, so we have some great women here. So I don't feel like I'm female here. It's just, I'm a member of the faculty. And I think that is what's ideal, where it's not really about your gender. 

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