Digging into Social Data—Indicators & Context Clues
A savvy analyst can draw conclusions even when the data they’re presented with is limited in scope or volume. While these conclusions come with limitation disclaimers, they still offer a valuable point of consideration when you’re developing your campus strategy and identifying which problems are most in need of solutions. Research Manager Amber Sandall and Client Success Manager Beth Miller share what our analysts look for in social data when the answer to their research question isn’t always obvious at first glance as well as some specific ways that social data can inform campus decision making.
First, let’s define two important terms social listening analysts regularly employ when analyzing data.
- Indicators are limited observations within a dataset. These observations are limited, for example, in volume or frequency, while still meeting your threshold for significance in your dataset. Though individually they may not seem important, when reviewed collectively they may indicate a larger pattern or insight analysts can use to draw conclusions. Indicators are typically primary observations from your dataset.
- Context clues are secondary observations that enhance your understanding of your primary observations from your dataset. Context provides the landscape to understand your data, layering in the subject of your research and others who may be invested in it, the environment from which you gathered your data and in which it’s being analyzed, and secondary research and expertise that places your research within a body of already completed studies.
Let’s build these terms out with an example.
Say you’re at a new friend’s house, and they have a full bowl of fresh apples on their counter. Just from this observation, you may not feel comfortable drawing the conclusion that your new friend really likes apples—after all, you just met them and there’s a lot you don’t know.
You learn another point of information shortly after you arrive—your new friend lives alone. This contextualizes your observation about the apple bowl, and you start hypothesizing: if they live alone and have this big bowl of apples, maybe they really do like apples that much.
At this point, know that for every individual and project, the number of indicators and context varies to form a valid conclusion. Some people may say, once they know their friend has a huge bowl of fruit and lives alone, that that’s enough for them to conclude their friend loves apples.
Others may continue seeking information (Campus Sonar analysts tend to!)—because your friend may actually have a regular guest over and the bowl is a courtesy for that individual. You can’t really say, but shortly your new friend states how excited they are to have met you, since “they’re brand new to town, and haven’t met many people yet.” Point against your hypothesis of a guest who loves apples.
Finally, you notice their fridge displays several photos that intrigue you. One is of your friend at an apple orchard, another of them at Halloween, dressed as (you guessed it!) an apple. In real life, you’ll likely ask if they love apples and quickly find out the answer. For the sake of this post, we uncovered several indicators (full bowl of apples, photos on fridge) and key context clues (living alone and new to town) that allowed us to draw a conclusion that, indeed, your new friend loves apples.
A skilled analyst is able to piece indicators and context clues together to draw your eye to potential themes and additional areas of exploration within social data. They may observe a handful of individuals across two social sites talking about the same topic. Does that mean it’s something our campus client needs to be aware of? The analyst will consider context, like current events, time of year, individual affiliation with the campus, and other items to triangulate what the observation could mean.
The ability to assess indicators, identify context, and triangulate data points are valuable skills for an analyst because they mean the difference between our clients receiving a report full of numbers or a report full of meaning. In a campus context, the apples example can play out in a similar way. An analyst who is deeply familiar with a campus’s conversation could see a handful of vague references from students like “can’t wait for Friday” or “see you later this week.” Armed with these indicators, the next step is to seek context. A look at official accounts doesn’t yield any additional information about what event might be coming up, but the analyst knows the frequency of these references isn’t coincidental.
They also notice a prominent alumnae posting that she’s looking forward to visiting her alma mater. And a student group posts a registration notice for a mentorship event. So how does an analyst know to pay attention to these seemingly disparate pieces of information? Over time, they develop a familiarity with the cadence, rhythm, and subjects in a campus’s usual conversation, and intuitively recognize when something departs from that norm.
A little more digging fits the puzzle pieces of indicators and context clues together and uncovers a student-run event that is bringing a high profile graduate back to campus to talk to interested students about her successful business. (And while ideally an institution would know about an event like this, anyone who has worked on campus recognizes that these things can and do happen under official radar.)
Once your campus teams are aware of this event, you can reach out to the student organizers to offer support, amplify their messaging to a wider audience, and engage your alumni office to coordinate a thank you gift for the speaker. Maybe this event helps reinforce some of your brand messaging around entrepreneurship and the value of a degree from your school. Or it provides a chance to highlight student initiative and creativity. Have a photographer at the event and show off a vibrant campus community. Each of these opportunities would be missed if you didn’t first piece together the clues.
Analysts can also pick up on indicators of emerging conversation trends over time. As they identify topics that are new to your campus conversation, they can monitor them for growth or change over time. In a positive context, this can identify areas of importance to your community; alternately, it can serve as an early warning when a crisis is on the horizon.
We’re grateful to work with analysts and strategists here at Campus Sonar that can identify indicators from social data, apply context clues, and uncover meaning for our clients—it’s a core part of the work we do for our clients, beyond finding relevant social data and reporting on numbers. We’re curious too: what kinds of indicators are you finding in your social data? Are you able to identify the context around them? If you’re doing the social listening work yourself, we created a cheat sheet that can help. Of course, our team is always thrilled for the opportunity to dig into a social listening project with you!
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This post originally appeared on Campus Sonar's Brain Waves blog.