How to Create Reactive Content That Engages Your Audience
By Nico PrinsOct 16
Published April 9th 2019
As a social analyst, exploring unfamiliar communities can be fascinating – you’re essentially looking at a mini culture with its own norms, etiquette and language.
In my work for Brandwatch React I’ve studied all kinds of communities, from Beliebers to Bronies. But my work barely scratches the surface of the level of insight our Strategy and Insights team can glean when they work on longer term projects for our clients.
Fascinating as it might be, generating insights from these groups is made hard by the lingo they use. The words particular communities use are important for their social cohesion, and often a word will mean something to one community and something very different to another – it’s part of what makes them different and what indicates that someone belongs. If you’re not speaking the right language, you could be chastized by or eliminated from the group.
When a person joins an online community it can be hard to adapt to the new language.
Let’s take Mumsnet as an example. It’s the UK’s largest and most active forum for parents, bringing in 14 million monthly users and 1 million posts a month. It’s huge, and yet if you’re an outsider it can be really difficult to understand what’s being discussed.
A brief scroll of their acronym list, which contains 131 translations, will show you just how insular (language-wise) the community can be.
Here are a few examples:
DFIL – darling/dear father-in-law
EWCM – egg-white cervical mucus
POAS – pee on a stick
STBXH – a soon-to-be ex husband
WOHM – a working out of the home mother
Some terms mean something different depending on the context:
EBF – exclusively breastfeed(ing) or extended breastfeed(ing), depending on context
Meanwhile, like I said above, some words can have different meanings depending on the community. Sentiment is a good way to illustrate this. “Sick” in a community discussing common illnesses among children is going to mean something very different to a community of skateboarders. And the meaning of “sick” will obviously depend on context when it comes to communities of skateboarders that discuss common illnesses among children.
So, when you’re about to start researching a community you’re not familiar with, how can you go about learning the lingo?
I spoke with Jack Mulholland of Brandwatch’s Strategy and Insights team to see what practical steps he’s taken to get his head around the lingo of communities he’s studied.
Scrolling through the mentions on a particular forum can make a good starting point for familiarizing yourself with the nuances of language. Using an automated tool that surfaces common words and topics will be helpful here.
Often it’s tempting to jump straight into analysis mode, but actually getting a feel for the words and rhythms of conversation can be great for starting out, especially if you’re building rules for the data.
It’s helpful to do this outside of a platform, too – meaning, actually visiting the site. Looking at a site’s “about” section to understand the purpose and backstory, as well as the type of community that might visit it is a good way to find out more about the internal workings and narratives.
Resources like Mumsnet’s acronym list are common among specialist communities.
If you’re looking into a subreddit you’ll often find a bar with rules and advice for posting on the side – check this out for help.
An example is one of our favorite subreddits, r/dataisbeautiful. Acronyms like [OC] are used to indicate that the poster was the original creator of the content.
Meanwhile, on r/gameofthrones there’s a detailed guide as to how to label potential spoilers. At first glance, these tags might seem totally meaningless.
Whatever communities you’re studying, take a look at the guidelines they and the wider internet provide to help with particular language.
As we’ve said already, many sites will have their own languages and signifiers of sentiment.
“Maybe this is a sense of self-preservation on my part,” says Jack, “But using common sense and human understanding can be powerful compared to AI which can trip over the non-standard language.”
It’s true that machines who are not used to the nuances of a particular community can struggle with automatic categorization when it comes to things like emotion and sentiment. This requires a bit of human interference and manual work, but often once rules are created that allow for this things will be smoother.
Thanks to Jack Mulholland for his input on this blog post. You can check out more of our Analyst Problems series here.