Sanders in June: Polarizing...Except in Media
Rusty Guinn
June 13, 2019·Politics
Sanders Narrative Map as of May 31, 2019
Source: Quid, Epsilon Theory
Sanders Narrative Commentary
- Of all major candidates, Sanders coverage demonstrates the highest attention, the highest cohesion and the highest sentiment (although sentiment relating to coverage of Pete Buttigieg, who has emerged somewhat in May and June, rivals that of Sanders).
- The high cohesion - visualized by the overall compression of distance between nodes and clusters in the graph above - indicates high similarity of language across articles referencing Sen. Sanders. Authors' references to Sanders follow a structured taxonomy and almost obligatory references to his age, socialism-related terms and his 2016 campaign.
- We think this alone justifies significant caution when reading news about Sanders and his campaign. We think the gravity of the strong Sanders narrative has the capacity to skew the language and implicit/explicit conclusions included in news reports in the direction of that narrative.
- Discussions of democratic socialism, the green new deal and related topics concerning universal health care, workers rights and unions, taxing the rich, etc. all occupy the most central, most connected part of Sanders's narrative. At this point in the campaign, the Sanders narrative is not only more cohesive than that of other candidates, it is cohesive around key issues.
- Those key issues and the language used to discuss them happen to be the ones that the media have been most engaged in writing about - popular democratic socialist policies are central to the narratives of the Democratic primary - which is the driver of Sanders's very high attention score in our system.
- There are only two central clusters within the Sanders graph that are remotely negative: the first includes articles defined by 'old white guy' language, usually expressed with concern about dual standards in discussions of electability and likability of Sen. Warren and Sen. Harris, in particular. The second are discussions of Sanders's remarks on Israel and Netanyahu.
- From a 'predictiveness' perspective, we think it is more difficult to judge how much the influence of media will be on a candidate like Sanders, who has a history and has established "opinions" from many likely voters. Still, the media is (intentionally or unintentionally) promoting common knowledge that "Sanders is the candidate with the policies that will make America America again." We are less convinced than some that voters still turned off by the 2016 primary or by Sanders's socialist credentials won't be affected.
Sanders Narrative Attention as of May 31, 2019
- Attention of coverage on Sanders declined somewhat in March with the entrance of additional candidates; since that time, however, it has remained stable and still well above that of nearly all other candidates.
- For most of 2019, populist and democratic socialist-related topics and language have dominated election coverage, which we suspect is the main reason for Sen. Sanders's attention measurement under our methodology.
Sanders Narrative Cohesion as of May 31, 2019
- With the exception of the period prior to his formal announcement of a 2020 campaign, the cohesion of coverage of Sen. Sanders has been both very high and consistent.
- We think that the narrative of Sanders - the 'socialist' candidate with a very progressive policy history - is crystallized across media coverage, causing all pieces to veer toward mentions of those issues or the use of language consistent with that common knowledge, even on disparate topics.
- As noted previously, we believe the presence of such a cohesive narrative warrants extra caution when reading news about Sanders (from all parties, regardless of perspective on his candidacy).
Sanders Narrative Sentiment as of May 31, 2019
- Interestingly, the sentiment attached to Sanders coverage has steadily increased in every month of the primary campaign.
- This is an unusual pattern, and isn't reflective of anything happening more broadly with the mix of topics over these five months - it certainly isn't a pattern shared by any other candidate.
- It is, however, only five months. This rise could absolutely be a feature of some random relationship of Sanders to topics that were covered more positively. Still, as consumers of news, we would be concerned that this might be indicative of knowing or unknowing preferences on the part of journalists authoring stories or editors assigning coverage.
- Almost universally, we think consumers of political news - supporters and opponents of Sen. Sanders alike - should be asking "Why am I reading this now?" for almost every Sanders article they read.
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Comments
Or it could be that the media’s audience is so small and unrepresentative that it doesn’t matter. For example, Fox News gets about 2.4M daily viewers. The NY Times has about 3.5M digital subscribers and maybe 1M print subscribers. AOC has 4.3M Twitter followers and 1.8M IG followers. Donald Trump has 61M Twitter followers.
Brad Parscale, Trump’s Digital Campaign manager’s goal is to have 80M FB/Twitter followers who, when requested will share/post/like a post. This enables them to reach followers and friends of followers more specifically with more personalized messages at virtually zero cost. I.e. they don’t have to buy political ads to reach their constituents. Maybe there are restrictions placed upon political ads in FB, but they won’t effect people sharing/posting/liking posts.
In the last election, there were 131M people who voted and 61M who voted for Trump. If Parscale can get to 80M people who will share/post/like etc upon request, they probably vote and encourage their friends to vote. If Sander’s buys media coverage/stories/publicity to organizations like the NY Times that have maybe 4M or so people who see unpersonalized content in mass media, what does it matter? Does it matter when they see it?
They are bringing a knife to a gun fight
This is a common talking point, but I personally don’t think it stands up.
Most of what is shared even through those methods IS a link to or deeply related to some specific piece of content, whether it is sponsored content, misinformation, a blog, a NY Times article or something else. The DJT Facebook page built posts around a Washington Examiner article, a Daily Caller article and a NY Post article in the last day alone. Some dozen blogs riffed off of every single one of his Tweets/Facebook posts. We include all of those types of sources in our universe.
More importantly, we think it’s important to think about common knowledge as something other than “how often is something shared.” That’s why we don’t focus on the volume of coverage. Even if we don’t have all the transmission vectors, we can still see the evidence of their influence on the structure of narratives within our dataset - and we believe there are deep feedback mechanisms between both formal and informal actors.
But missionaries are a thing, and they matter. Focusing on subscription levels misses the point, IMHO.
Does your analysis do any kind of weighting of individual articles, or does each one stand on equal footing? Whether by viewership, shares, or whatever.
I wouldn’t try to argue that one way is better than another, but it seems like there’s a whole universe of different angles on the data. What constitutes a salient cluster could have different outcomes depending on one-article-one-vote, one-publisher-one-vote, one-reader-one-vote, etc.
You make excellent points, especially about the missionary supplying original content and your analysis of it. The concept I’m struggling to understand pertains to a second measure. Where content is selected for effect, personalized and slanted in a different direction and then rebroadcasted to much larger audience.
If the NY Times’s reach ends around 4M subscribers, at which point they lose control of their message and other people leveraging social media, repurpose it and broadcast to 63M+; isn’t that medium, it’s reach and it’s ability to repurpose a message also important?
To be sure, social media is critically important. Scraping that data has proven to be mostly trivial, but analysis of it is also rife with Type 1 errors. Because we are focused on meaning, we think it is entirely possible to understand a great deal about understanding social media simply by acknowledging that the purpose of much content creation is transmission through those vectors, and much of the rest is informed by the implied common knowledge from them.
But the main thing that informed our thinking is this: social media scraping is very effective at telling you what people think (and what they want others to think about them), but that isn’t what we’re concerned about. We are concerned with common knowledge - what everyone thinks everyone else thinks. There must be a natural perception that everyone (or at least everyone within some group) else will have seen something to create a strong form of this. For this reason, we think cohesive content is either an indicator of primary missionary activity (creating common knowledge) or secondary missionary activity (repeating it because of the attractiveness of publishing things everyone thinks everyone thinks). The former captures ideas upstream of social media, and the latter captures ideas downstream, but in neither case would we be ignoring social channels’ incredible influence.
It’s a big driver of the panopticonesque power we think has accelerated all of these things we write about.
We struggle with it, in part because common knowledge - what everyone knows everyone knows - in the wild can be either inductively or deductively derived. We can observe common knowledge by identifying closeness of language, or we can hypothesize that certain parties are missionaries and observe what they are saying and how it resonates. In general, it is our theory that volume measures tend to tell you what people are seeing and what they think themselves, but not necessarily what they believe that the crowd believes. That’s a bit different when something shows up in the NY Times vs. social media, of course, and for many of our analyses (the financial research in ET Pro sector analyses, for example) we do some of what you are describing by explicitly limiting our universe of sources. It’s not ‘weighting’ per se, except inasmuch as it is weighting non-major publishers at zero. So we do combine both approaches to diversify the universe of angles at which we approach the question.
For politics, however, our observation was that different channels have native tendencies that would bias the results if we adopted a similar approach. Anecdotally, I have looked at our results so far, and other than cutting off certain candidates entirely (due to inadequate content), view/share weighting or source importance-truncation don’t appear to really change the rank ordering on our key metrics all that much. We’ll keep eyeballing that in case they diverge, and if they do we’ll be sure to publish it (since the reasons, I suspect, would be telling us something very interesting).
Thank you, I had not considered the panopticon angle. In fact the participants rebroadcasting want to be observed and belong to a movement. It also amplifies an idea Timur Kuran articulated in his book “Private Truths, Public Lies”. (https://www.amazon.com/Private-Truths-Public-Lies-Falsification/dp/0674707583/ref=sr_1_1)
My aging brain struggles to fully understand the method of narrative analysis Ben and Rusty apply. However, MY interpretation is that they aren’t quite yet sure ( but will get there I think) of how to interpret the quid data to political issues either.
For when they apply Greenspan-ion double, triple negatives to their conclusions they are either 1) not sure of the interpretation or 2) want to make the reader unsure of what they mean.
I prefer to believe the former.
I am quite pleased that this quid approach has been discovered and that I am ( slowly, very slowly) understanding it.
Oh, and quite happy that my lexicon gets to grow on almost every article.
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