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Analytics Quinnipiac

Quinnipiac Assignment #02 – Qualitative and Quantitative Analytics

Quinnipiac Assignment #02 – Qualitative and Quantitative Analytics

This week’s assignments at Quinnipiac were centered around the differences between quantitative and qualitative analytics. I had a couple of essays to write.

I have decided to reprint one of my essays here, in its entirety.


Qualitative versus Quantitative

I think that a choice between the two is, perhaps, misplaced.

English: Interactive Visualization of Qualitat...
English: Interactive Visualization of Qualitative and Quantitative data in a web based mixed methods application (Photo credit: Wikipedia)

Aren’t both of these necessary, in order to really see the big picture?

We Love Quantitative Data

Probably the best part of quantitative data is that it’s relatively easy to obtain, particularly online. Consider this – do we, given the current state of technology, know everyone who comes into, say, a department store?

Web analytics framework
Web analytics framework (Photo credit: Beantin webbkommunikation)

Even when we break this down to hourly increments, and even if we look at closed-circuit cameras, we still might miss someone. After all, if a person leaves and comes back later, we might not notice that it’s the same person.

Not so with the web. Cookies and other tracking codes give us the ability to know that a device has returned; and an account if our site allows for user accounts. That still doesn’t help us if everyone in a household uses the same account, but it’s a start.

We look at our web data and we think – aha! User #12345 has returned four times in one day!

And then we have no idea why that happened, and no way to capitalize on it. It’s the ultimate in vanity metrics, e. g. it’s stuff that can be measured but it isn’t necessarily actionable, or even desirable information.

We Love Qualitative Data

With qualitative data, we get more into the whys and wherefores.

coding cat-egories
coding cat-egories (Photo credit: urbanmkr)

Why did User #12345 return four times in one day? If a purchase is made on the fourth go-‘round, that’s terrific. But why were there three other visits? Even someone performing research and then returning later might not necessarily visit two more times. What’s up with that?

Maybe the website was slow those two other times. Maybe User #12345 got busy and abandoned the cart for Visit #2 and Visit #3. Some of this is inferential. Some of it can be proven, such as site slowness or at least traffic spikes that could imply speed issues. We can’t get into User #12345’s head (at least, not yet).

We REALLY Love Them Together

I think we’ve got to look at the two types together.

In the Huffington Post article, The Big Data Craze Is Just as Qualitative as It Is Quantitative?, Sean Donahue writes, “But for brands, political campaigns and advocacy organizations that aim to have data-driven conversations with audiences, it will be more important than ever to apply qualitative logic and human reasoning to online analytical models. In short, subject matter expertise and deep knowledge will matter more than ever before given the rise of big data.

As communicators, even with what we have at our fingertips today, we need to immerse ourselves in the substance that contextualizes big data and allows us to make sense out of it. This means committing more time, asking more questions, consuming more content and never losing sight of the fact that data without actionable insights is meaningless.”

I believe that what Donahue is saying is that we can and will be getting great big garbage bags full of data, and soon even more of it will be at low or no cost. But without contextual analysis, it’s somewhat meaningless.

Further to that is Anmol Rajpurohit’s point in Qualitative Analytics: Why numbers do not tell the complete story?, wherein he writes, “Quantitative analytics still needs more manual intervention and the results are often fuzzy. In absence of a clear-cut approach and thus automation, it is not as time and energy efficient as the traditional quantitative analytics. But, qualitative analytics is still indispensable as it provides deep, actionable insights about the ‘why’ and ‘how’ aspect, which often gets ignored as we continue to be inundated with the ‘what’ ‘where’ and ‘when’ of statistics.”

As Rajpurohit indicates, qualitative data is fuzzy and manual and not automated. It’s a slow process (and perhaps a less exact science than quantitative), yet it remains necessary to a holistic understanding of online data.

06/30: It's Peanut Butter Jelly Time!!!
06/30: It’s Peanut Butter Jelly Time!!! (Photo credit: ttyS0)

To me, this is peanut butter and jelly. They’re fine separate, but they work best together. With purely quantitative data, we can know that a particular literary passage has 278 words. We can know that two of its longest words are twelve letters long: consummation and undiscovered. We can find that the (probably) most frequently-used word is ‘the’, with twenty occurrences. With qualitative analysis, we learn that the mystery passage is Hamlet’s To Be or Not to Be soliloquy. With qualitative analysis, it stops being a laundry list of words, and its context affords a meaning that goes beyond bare statistics.

References


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Opinion Twitter

Bruins denounce Twitter Hate

Bruins denounce Twitter Hate

According to USA Today,  the Boston Bruins organization quickly moved to denounce the racist tweets that surfaced in 2014 when Canadien PK Subban scored a winning goal against the black and gold in overtime.

Bruins denounce Twitter Hate

In a statement, Bruins President Cam Neely said, “The racist, classless views expressed by an ignorant group of individuals following Thursday’s game via digital media are in no way a reflection of anyone associated with the Bruins organization,” 

Twitter is, I feel, a wonderful medium. But it also has a capacity for speedy publication of half-thoughts. It seems, sometimes, to be a nearly perfect medium for rapid fire hate speech. What, if anything, could be done? How could something such as this incident be prevented in the future?

Subban was targeted for his race. Certainly Bruins fans were angry about their team’s unsatisfactory outcome. Yet the response was absolutely and completely out of proportion to the offence. In fact, it was thoroughly misplaced. Disappointed sports fans of course have the freedom to speak their minds. There is really no law or rule against becoming emotional, or even incensed. Many, many sports fans have perhaps overly deep emotional investments in their beloved teams. But this was different. In this instance, Subban was set apart, isolated, and attacked for not the color of his jersey, no. Instead, Subban was the subject of Twitter fury due to the color of his skin.

What did Martin Luther King say? That he had a dream that, someday, his children would be judged, not for the color of their skin, but for the content of their character. Unfortunately, that day is not quite here yet, it seems.

What do YOU think?

 

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Analytics Quinnipiac

Quinnipiac Assignment 01 – Qualitative and Quantitative Analytics in my Life

Quinnipiac Assignment 01 – Qualitative and Quantitative Analytics in my Life

Quinnipiac University
Quinnipiac University (Photo credit: Wikipedia)

I began a new semester at Quinnipiac University; this new course is on social media analytics, which includes Google Analytics plus the collecting and interpreting of actionable data.

My professor is Eleanor Hong, who was also my professor for Social Media Platforms. I had really loved that class, so I made sure to take this one with her as well.

Our first assignment was to create a video. I was very pleased to see some names that I knew who are taking the course with me and I had originally met in Social Media Platforms. My final project partner from that course, though (Kim Scroggins), is graduating later this year and is instead just taking a Master’s Degree capstone project credit course. I have to admit that I do miss my final project partner a bit!

It already looks like it will be an interesting course. This video is about quantitative and qualitative analytics that I use in my daily life.

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Opinion Twitter

#AmazonCart Debuts

#AmazonCart Debuts

#AmazonCart Debuts as, according to Boston.com, Amazon.com has partnered with Twitter to help simplify the Internet shopping experience.

#AmazonCart Debuts

The #AmazonCart hashtag was officially introduced in early May, encouraging Twitter users who see tweets of products sold on Amazon.com to reply with the hashtag, which then puts those items in the users’ Amazon shopping carts.

The enormous online retailer’s website has detailed instructions on how to connect your Twitter account to Amazon.com, which is evidently a vital step in the process.

Would you do it? I’m not so sure I want people to see if I am buying lingerie, medical supplies, or self-help books. Imagine a potential employer seeing a purchase of cross-dressing supplies, or The Communist Manifesto, or any number of anti-aging products. What if I were investigating products to help me get a divorce, get through chemotherapy, or file for bankruptcy?

If I keep my age (and any attendant clues about it, such as my graduation years, or the earliest versions of software that I claim to be an expert regarding) off my resume, does not the purchase of menopausal relief supplies make it something that a potential employer could reasonably infer? Here in Massachusetts, a credit check is not supposed to be permitted.  Yet if I purchase a book about improving my credit score, would not a potential employer put two and two together? Of course, there is the possibility that I am overthinking this (I have been known to do that before). But still!

Methinks the Internet already knows plenty about my spending habits. I can take the extra five minutes or so and use a regular shopping cart at Amazon. And no one will ever need to know I’m buying disco albums.

Oops ….

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Quinnipiac Assignment #15 – Reflections about ICM 522

Quinnipiac Assignment #15 – Reflections about ICM 522

With the end of my first Social Media class came a request for our overall impressions of how things went. Hence, I prepared Quinnipiac Assignment #15 – Reflections about ICM 522.

Quinnipiac Assignment #15 – Reflections about ICM 522

My classmates and I were also tasked with showcasing what we felt was our best work.

I was so very pleased that I had a few works to choose from, but I narrowed my choices down in order to save some space.

My reflections essay included comments about the video and essay portions of Module #4, Module #9, Module #10, Module #11,  and my Final Project; that video is duplicated below.

Module Four was about the Ad Astra Star Trek fan fiction writing community. Module Nine was about the Facebook page that my partner, Kim Scroggins, and I created for our ‘client’, the as-yet undiscovered Rhode Island rock band, J-Krak. Module Ten was about the creation and growth of the Twitter stream that we made for J-Krak. And Module Eleven was all about our less than successful experiments in spreading the gospel of J-Krak to MySpace and Google+ (the former was a particularly abysmal showing. At least our client’s presence on Google+ assured better placement in overall search results).

The class was great fun, and I could not get enough of studying for it. I have never, ever had a course like this before, where I was so into it that I could not wait to study, and I did all of the extra credit because I wanted to, and not because I necessarily needed to. That has never, ever been my experience with a class before this one. This overwhelmingly positive experience has given me the incentive to not only finish my Social Media Certification training, but I am also rather seriously considering going on and getting my Masters’ Degree in Communications, with a concentration in Social Media.

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Opinion Twitter

Twitter bigots have no place in Boston, says NHL

Twitter bigots have no place in Boston, says NHL

On May 3rd, 2014, ESPN reported that the Bruins and their coach, Claude Julien, are appalled by recent racist tweets against Canadien PK Subban.

Boston Bruins
Boston Bruins (Photo credit: Wikipedia)

Subban’s winning goal against the Bruins sparked Twitter outrage that turned racist very quickly.

While fans were angry afterwards, and some threw debris, the organization says that the racist outrage doesn’t seem to have come from the fans who don black and gold and attend the games.

“I didn’t hear anything from the fans — at all,” said Bruins forward Brad Marchand. “It’s all Twitter.” 

When asked whether he’d heard racist comments while on the bench, Julien said, “Not to my knowledge, no. There’s a lot of good fans out there, and that’s the sad part about it is that your good fans get tarnished because of a couple of comments like that who don’t belong in that same group.” 

With social media moving almost as fast as the speed of light (or so it seems), anger is the emotion that moves the fastest.  Couple it with racism, and it all seems even more accelerated.

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Quinnipiac Assignment #14 – Final Project ICM 522

Final Project ICM 522

These videos together comprised our final project for Quinnipiac’s Social Media Platforms class, ICM 522.

Final Project ICM 522

At this point in time, I have a short break before starting ICM 524, which is the Analytics class. I am taking it with the same instructor, Professor Eleanor Hong.

In the meantime, here are our project videos.

My partner, Kim Scroggins, went first. I would love it if you could take the time and watch her video, too. We were a true team and really enjoyed working together.

And now here’s my half of the presentation. One of the things that I made absolutely sure of doing was to thank my partner. This was absolutely a team effort and it would have turned out far differently if we had not gotten along as well as we did.

We went over our general experiences with J-Krak and the many social media platforms we tried. We made every effort, I feel, to engage our audience and garner buzz and attention for our ‘client’. We set ourselves up for a rather difficult task, which was to try to get a small measure of fame for a rock band that was not even online in any way, shape, or form when we first started this project.

MySpace was recalled as a failed experiment. Google+, for the most part, was a failed experiment in engagement, but it did help us with improving our search engine optimization efforts. Twitter and our blog were somewhat in the middle. Twitter worked out fairly well as we were able to join the overall conversation. However, the number of our followers remained fewer than the number of people we were following. The blog had an ever-increasing number of followers, but we received few comments. Our best social media platform? Spoiler alert – it was Facebook.

Thanks for watching! Next week, I’ll post my impressions of the class overall.

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