Big Data as a Communicator

Article 5 min
Even with high-tech tools, data management requires time and commitment. Communicators need to know how to navigate, measure and contextualize the numbers.

In an age of information overload, now more than ever communicators need to take cues from data analysts to better understand public opinion and breaking news. Whether the actual data analysis position is contracted out or not, public affairs professionals and communication strategists can benefit from an overview of the data analysis process, so they are better equipped to synthesize and present the data to their command.

The Basics

Big data is the massive collection of individual data across digital platforms. Big data is defined by the 5 Vs: Volume, Velocity, Variety, Veracity and Value.

Click a target to reveal more in-depth information.

The 5 Vs of Big Data

Image of glowing data server, five circles with icons representing volume, velocity, variety, veracity, value.
Icon of large data cube surrounded by smaller data cubes to represent volume.

1. Volume

Volume is how much data you have. You collect volume data using AI.

Explore questions such as:

  • How much data is there?
  • How many people are talking about our organization?
Icon of data cube moving at a high speed to represent velocity.

2. Velocity

Velocity is how frequently data is generated based on the time period in which it's collected. You collect this data using AI.

Explore questions such as:

  • What is the period of collection?
  • What dates is this information from?
Icon of data cubes grouped up in three different formations to represent variety.

3. Variety

Variety is the data's type and structure; data can be structured, semi-structured and unstructured. You collect this data using AI.

Explore questions such as:

  • What methods are people using to talk about our organization?
  • What platforms are they using?
Icon of data cubes arranged in an evenly spaced grid. Glowing center cube with a checkmark and shield to represent veracity.

4. Veracity

Veracity is the accuracy and trustworthiness of the data; consider bots, trolls, etc. This data requires a human to decipher.

Explore questions such as:

  • Is the data accurate and trustworthy?
  • How much of the data is from real users in our target audience?
Icon of data cube presented as a shining trophy to represent value.

5. Value

Value is analysis of the data to determine how it can help your mission. This data requires a human to decipher.

Explore questions such as:

  • What is the takeaway from the data?

Volume, velocity and variety can be determined by artificial intelligence (AI) tools but veracity and value require a human to decipher. Thinking of big data through the 5 Vs framework may help streamline the process and narrow down information into more palatable chunks that you can communicate to your command.

How to Use Big Data

Once you know the basics, it is imperative to collect, leverage and present data accordingly.

Basic statistic skills are necessary to accurately interpret big data. If you aren't comfortable with this and there's a budget available, know that there are data scientists available to you. Large commands and the information operations community have embraced data scientists and a job series (1560) has been created to hire them.

Data analysts work with AI software to collect data. However, to use that data as a communicator, you need to be able to navigate social networks, make value and significance judgments and put that data into context. An AI cannot do that.

Synthesize the Data

Before you can start collecting data, you need a guiding question. What are you looking for? What does your command want to know from this research? Do social media posts align with communication goals? Is the social media account's goal to expose the audience to information or foster dialogue, or both? Consider undertaking a social media evaluation for jumping off points.
With a question to guide your way, you need a program to help you start collecting. There are a plethora of listening and monitoring tools, both free and priced. Leverage your tool(s) of choice to track topic segments. Topic segments are ways of dividing larger influxes of information into smaller groups, based on similarities. For inspiration, look to upcoming releases, discover or analyze popular conversations on social media and what leadership is focusing on. Use these tools to create Boolean searches within your tool for terms related to your question.
Next, you'll need to set a reporting period. It's unreasonable to track all of the data and conversations about your organization, so set a time frame that is long enough to illustrate changes but short enough for some specificity. Setting a reasonable reporting period helps you collect enough data points to see trends and get a sample size representative of your audience. For an environment that's changing rapidly, like a news cycle, a week could be a reasonable timeframe. Something likely to change more gradually, like public opinion, could widen the reporting period to a monthly basis.
Once you have enough data, you can extract data files using your tools. Know the differences between tools, especially if you're using the platform-specific analytics tools on social media. For example, Twitter's trending hashtags are a completely different system from a TikTok "For You" page. Even platforms owned by the same company, like Facebook and Instagram, are not necessarily interoperable.

There are also legal and ethical implications to consider, as monitoring an individual is prohibited. 5 U.S.C. § 552a(e)(7) requires that agencies “maintain no record describing how any individual exercises rights guaranteed by the First Amendment unless expressly authorized by statute or by the individual about whom the record is maintained or unless pertinent to and within the scope of an authorized law enforcement activity.” What you can track, however, are common discussions and topics among your audience.

Think of data collection like you're a scientist tracking changes in marine life. You don't catch individual fish, and you can't dump the entire ocean onto the boat. Instead, get a sample that represents a larger trend. Topic segmentations are like casting a net to get an idea of an overall trend or discussion. Try looking at how many people use a specific hashtag or term. Observe the context of how the hashtag is being used: negative, positive or neutral. You won't be able to look at each individual post, but this will give you an idea of how your target audience is discussing topics relevant to your command.

If you do have access to a data scientist, make sure you maintain dialogue between them and the communications team to brainstorm/exchange topic ideas. Look at what people online are saying—public reaction is often intertwined with your organization's response. Some topics are reactive and some topics are proactive, so keep an eye out for upticks in activity. That way, you can describe what you pick up on to command while peeking around corners for what might be ahead. As topics arise, the time comes to present your findings to command.

Present to Command

Odds are you are initially looking at a long spreadsheet or table with all of your data, but this isn't what your command needs or wants to see. Remember, your command needs to be brought up to speed quickly, with visuals and essential information that answers questions. Don’t just screen cap percentages or read off a page; interpret.

Go back to your original question and decipher what the command wants to know and what they need to know. Organize the data around your original question and any subsequent questions that they might ask.

If your original question is "What is the sentiment around appearance standards in our service branch?" then other questions might be:

  • How much of our audience is aware of specific appearance standards?
  • Why do people like/dislike appearance standards?
  • What is the impact of appearance standards on our mission?
  • How can we better inform our audience appearance standards?

Visual presentation is another essential report component. Look at the data and the sampling rate (daily, weekly, etc.) and whether it suits a graph, line chart, pie chart or a simple spreadsheet. Be transparent and upfront about the sample and limiting factors.

At the end of the day, the best way to present information depends on what leadership wants to know. Arranging data based on what they're looking for will keep reports concise and translate your hard work into actionable change—change you may be able to see as you listen to the next social media conversations.


Simplilearn. (2019, December 10). Big data in 5 minutes.

Wiencierz, C. & Röttger, U. (2018). Big data-based strategic communication. Communication Director.

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