Crunching the Data When Your Post Goes Viral

Singer-songwriter Marian Call wanted to write about our changing relationship to work. She sent out a quick tweet to her followers asking what their first jobs had been before she went to sleep.

What were your first 7 jobs?   Babysitting, janitorial, slinging coffee, yard work, writing radio news, voice-overs, data entry/secretarial   — Marian Call (@mariancall) August 5, 2016

Call woke up to find her tweet had gone viral and she got replies from many people including some celebs like Buzz Aldrin (Dish washer, Camp counselor, Fighter pilot, Astronaut, Commandant, Speaker, Author) and Sheryl Sandberg (1. Babysitter -twice – Office receptionist, Salesperson in clothing store, Aerobics instructor, World Bank health team, Children’s Defense Fund).

Marian did not use a hashtag but tag emerged and that made it easier to see responses. Unfortunately, different versions were used and are still active, like #firstsevenjob or #firstsevenjobs and #first7jobs. And the query and tags also appeared in other networks like Facebook.

She was interviewed on the Make Me Smart podcast  and she explained that then needed a way to to crunch the data from all the Twitter responses.  She was contacted by the social product manager at IBM who had heard her interviewed and they put the data into their Watson supercomputer and then were able to produce an infographic of the data.

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The data shown is interesting and shows commonalities across the world. Of course, we can’t manipulate the data or request other queries. Call said she would have preferred a spreadsheet she could sort and search.

This little exercise points out one flaw with Twitter and many other social sites – no easy way to pull user data and draw conclusions about it. There are paid programs and people who can do those things for you, but a free, built-in way to do those two tasks is not reality.  Most of our posts will not go viral, but even gathering the data from a normal social media campaign can be difficult.

Marian’s experience did get others to try their hand at the task without a supercomputer. One example is at blog.monkeylearn.com/analyzing-first7jobs-tweets-monkeylearn-r/

Can We Measure Social Media Sentiment?

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Social media sentiment is the perceived positive or negative mood being portrayed in a social media post or engagement.

If you could track sentiment accurately, it would help you understand the person’s feelings behind the post. As a marketer, this would be very useful, but would also be useful for individuals.

Certainly, there is sentiment behind every post. But can it be measured with any certainty?

There are scholarly articles about social media sentiment and a good number of companies that are working on trying to measure sentiment, which you might also see described as sentiment analysis or opinion mining. By any name, this is the analysis of the feelings (i.e. attitudes, emotions and opinions) behind the words.

Most of the tools use natural language processing. Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) languages.  It allows you to talk to your phone or some device in your home or car. These devices can understand your words (usually), but can they read your emotions? When you ask for directions are you angry, tired, frustrated or in a wonderful mood?  When someone responds to an offer posted in social media by a company by saying “This is crazy!” is that a good kind of crazy or an insanity crazy?

In social media, this is analysis that goes beyond Likes, Shares or Comments. Did people respond to the original post in a positive, negative, sarcastic, humorous or biased way? A human reader may be able to discern that, but can a tool do the same thing for hundreds, thousands or millions of posts?

The  complexity of emotional responses makes this analysis difficult. You have heard a lot lately about sites like Twitter and Facebook being told that they need to better monitor hate speech in their networks. How do you do that? Rely on users to report it? Have other humans monitor it? That won’t work when every second, on average, around 6,000 tweets are tweeted on Twitter, which corresponds to over 350,000 tweets per minute or 500 million tweets per day.

You need technology, but technology is famously not very good at reading human emotions.

There are some simple tools that some of you might already use for analysis.  Hootsuite Insights and Facebook Insights and SocialMention are some of the easy and more common free(mium) tools for analysis, but they are lacking in the analysis of sentiment. Many businesses and individuals use Google Alerts as a simple way to monitor their name, brand, and to track “content marketing” with the result being emailed as they occur, daily or weekly.

We are still a good ways off from a time when some combination of NLP and AI can read the sentiments of social media posts accurately, but the desire and need for it only grows more critical as networks grow.

Dark Social

Social media is all about sharing. But more and more social sharing isn’t being shared. That is, some content on social networks is being shared with a select audience rather than the general public or all users on a network.

For example, if you are using Snapchat or most messaging applications, your content is probably shared with as few as one other person and perhaps only your own circle of followers. This is not so unusual. You probably have made settings in Facebook so that not all of your posts and photos are visible to the public or even all of your Facebook friends.

I have seen estimates that almost 70 percent of online shares occur in what some people call “dark social.”

That phrase comes out of an earlier one – “dark web” – which is the part of the World Wide Web that is only accessible by means of special software. Using the dark web allows users and website operators to remain anonymous or untraceable. That is something that poses new and formidable challenges for law enforcement agencies around the world. These darknets, overlay networks which use the public Internet, which forms a small part of the deep web, the part of the Web not indexed by search engines.

Dark social (a term that doesn’t appear on Wikipedia yet – I did request an article be created a few weeks ago) is the one-to-one and one-to-few social sharing that happens in a space where analytics tools cannot track it.

Businesses may have to explore this area as their customers gravitate more to using it.

The Social Media Skills Gap

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Gap? What gap? Using social media for marketing, customer service and sales has fully arrived. eMarketer says there is 90% adoption. That’s not the gap.

The gap occurs in training and resources for employees. Some companies rely on a small team or even an individual to handle their social media. Of course, many companies outsource their SM management. There is nothing inherently wrong in that approach, but it is important for almost all employees to have a background in SM and an understanding of the organization’s strategies for using it. This is particularly true for companies that use/encourage/allow many employees to use social media for their work.

Employees have been largely ignored. Research from management consulting firm Capgemini Consulting says Some consultants have said that 90% of workers don’t have the skills to leverage social media as a business tool.

If you’re hiring, more social media courses are being offered at colleges (generally in marketing and communications programs), but there are also online courses available for current employees, including MOOC offerings and free on-demand resources from places like Hootsuite.

Targeting Niche Social Networks

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By definition, a niche is a smaller specialized subset of a larger set. People who do nude yoga would be a niche community compared to those who do any type of yoga. There are plenty of niche social networks that target a select segment of the general population. Every marketing person knows that being to target a more specific audience for your products that matches your desired user is essential. In social media, using niche social networks is one way to do that.

Anyone on the Internet knows there are plenty of dog and cat lovers posting to Facebook, Instagram etc. But those owners may also use Dogster , a social network for the dog lover and Catster for the kitty crowd.

Why should we as social media designers know about these niche networks? Because you or your clients definitely fit into some niches. Certainly, a pet store should be active in niche pet networks. This can be a place to share your expertise and drive readers to your own site.

I use Goodreads which is a well established site that connects readers.  It’s a great place to have a profile if you’re a bookstore, author or publisher.

Dribbble  is one of many niche sites for designers.

Interested in knitting and crocheting?  Ravelry and other online network for knitters and crocheters would also be a good place for fashion designers who work within these mediums.

Letterboxd is for the film buff and people have film diaries and share lists and connect with other movie lovers.

Restaurants, bars and clubs all have niche networks, such as Fubar which has over 9 million registered members. That seems like a big niche. Fubar claims it is the world’s largest online bar – an odd concept in itself.

The DIY audience is so big that it has many niches. Curbly is a broader DIY social network, and Instructables is a place to share what you make, whether that’s music, games, robots, woodworking or whatever.

The point is that whatever your particular interest or business focuses on, there are viable smaller networks than Facebook or Facebook groups to connect with people. You should broaden your own business “keywords” too. You’re promoting a neighborhood restaurant? Sure, you should check out Yelp and any area networks, but you could also consider posting some of your favorite dishes to a place like All Recipes. That is a very large recipe sharing network that DIY chefs will use, but is also a place for foodies. More than half of the people watching cooking shows will never cook the recipes. But they will look for those dishes the next time they are dining out.

Niche social networks make their money the same way the big networks do – advertising. But what they can offer is a very defined audience, rather than an ad broadcast to an audience containing many people who are not interested. yes, Google, Facebook and all the others do work on better understanding users’ tastes, but a niche network already knows its audience. A network such as Black Planet has music, jobs, forums, chat, photos, dating personals and groups all targeted to the specific interests of the Black community. If that is part of your demographic reach for your business or a particular campaign, that’s a good place to use.

 

Social Writing

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Image by Drew Coffman via flickr

I appreciate that in writing about “6 Underappreciated Skills for Social Media Professionals,” Evan LePage includes writing as one of those six.

If you do social media, you spend a lot of your time writing.  Short tweets and posts, captions and comments are all important – and not without skill and design when done well – tasks of a social writer.

The obvious writing task is blogging which is generally a kind of journalism, technical writing or an essay.

As the author points out, even our growing visual networks, such as Instagram and Youtube, require titles, tags and captions and those are all important factors to getting found online and pushing engagement.

I still have to point out to people that working online also requires a lot of reading. Students in my online graduate courses who are new to that kind of learning environment are often surprised (not happily) about the amount of reading and writing required to do well.

We are becoming more and more digital, but reading and writing are not going away, though they are evolving.