What this is…is not, & Some Methodology
By: Adam Meldrum
Tags: Social Media, Social Listening, Democratic Primary, 2020, Politics

Us

Here’s to trying to make this noncontroversial and easy to understand…that usually works well on social platforms right? :)

#1: We are Republican political strategists, and at least initially, this work will focus on the Democratic Presidential primary. It is non-partisan and focused on the data around the candidates as aggregated via social listening/intelligence tools.

The goal is to analyze how the conversation around the candidates evolves as the races evolves…trends, outliers, influencers, impact…etc etc…compare differences and similarities, and ultimately, predict who will win (kidding).

We think it will be fun and interesting. Hopefully you do as well.

In the future, we will focus on other political/news items that do not conflict with our work, and if they do, we will note it.

#2: If you have questions on what social listening/intelligence is here is an in-depth wiki to read. We will summarize more below.

A MAIN POINT: ***The data is public***

From Wiki:

“Social media measurement, ‘social media monitoring’ or social listening [is a way of computing popularity of a brand or company by extracting information from social media channels, such as blogs, wikis, news sites, micro-blogs such as Twitter, social networking sites, video/photo sharing websites, forums, message boards and user-generated content from time to time.”

Here is a recent article on how some financial/investment firms and brands are using this type of data.

“A growing number of financial services and investment banking outfits are looking at dashboards like those developed by Monatair, a London-based social media intelligence service whose clients include Credit Suisse. Using the platform, investors can bring up a column chart calculating, for example, Burberry’s social media performance back to February 2016, when it hit its peak for likes and shares.”

#3: The name, “Listening for the Secret, Searching for the Sound” is a lyric in The Grateful Dead song, Unbroken Chain. Proceeds generated through the Medium Partner Program from this work will be donated to HeadCount.org and/or The Rex Foundation.

#4: Via my work as a political/digital strategist, I have been using social listening/intelligence tools for the last few years to help understand the evolving conversation around my clients (political candidates & issues), specifically trying to measure media impact — both earned and paid.

OZY Media wrote a brief article about some of this work.

#5: As I tell clients, social listening/intelligence is not polling. These are not metrics from a voter contact program. And it is not simply a report you click “generate” to pop out.

It is based on executing keyword queries against a treasure trove of publicly available data across the webs of inter. (Twitter, Reddit, Quora, Blogs, Forums, Websites etc…)

All of the data from your query is pulled into a technology platform where it is filtered, normalized, and scored/analyzed across a number of predefined measurements categories such as: estimated reach, volume, total likes/shares, sentiment, influencer level, keyword trends etc etc…

From there, as an analyst, you take a deep dive into the data, filter/refine it, export it, graph it, compare it, etc…and allow it to shape a story. And ultimately, you define the story of the data with your narrative.

It is not perfect. It’s not right or wrong kind of thing, it’s simply a story.

Your story.

It’s also not the whole story…again…just “ahhhh” story.

So that’s what we are here to do. Tell a story now and then. (As opportunities come up, I will also be doing some network graphing.)

Disclaimer: There are very complicated and detailed practices that go into this work…the queries, the measurement, removing bias…and to that, I’ll be honest, we are starting by keeping this very simple.

Why?

Because we are doing this in our free time for fun. Over time, as we come across items that warrant a deeper dive, we will.

That said, initial queries are based simply on the full name of the candidate and we are comparing each candidate across independent queries.

Now, before data purists and analysts blow up the comments pointing out all the ways to expand, remove bias and/or improve the query, please note…we are happy to take suggestions and consider ways to incorporate your input if/when we are able.

So for now, please happily consume the data from that context and enjoy.

Thanks.