“The Silent Majority” is, according to Julia Kirby, a phrase that President Nixon used to describe the people who were not against the Vietnam war, who Nixon believed to be in majority, but were less vocal than the anti-war protesters. And during the 2016 presidential election, then Republican candidate Donald Trump claimed that he would win the election, despite the polls saying the opposite. Trump justified his claim by referring to the silent majority – claiming that there were far more Trump-voters than what the polls suggested.
The idea behind the silent majority is simple: the most vocal are not necessarily the majority. Kelly McNamara writes about the 90-9-1-rule about online communities, which states that 90% tend to be engaged but less vocal, 9% tends to be more vocal by commenting and sharing, and 1% tend to be the most vocal by creating new content. While the numbers may not be exactly 90, 9 and 1, the idea is simply that most engaged people don’t contribute. These are often referred to as lurkers.
Whether you call them the silent majority or lurkers, I can’t help thinking that someone is making a big deal about something that is actually quite simple: not everyone has a desire to expose themselves by contributing online, and we can’t know what everyone is thinking about something. The silent majority is not some organized, underground revolutionary force. It’s a statistical blind spot. It’s not knowing everything about everyone (thankfully).
Of course it’s interesting to look into why some people don’t wish to contribute much online. And it’s interesting to ask: how would things look if they did? If the internet is to be a democratic tool, then everyone should have the same opportunities to contribute. So if lurkers are not contributing because of some external factors such as fear of internet trolling or low digital literacy, then that is a problem. And it should be addressed.
Hi everyone, just a small update on my thesis (a big one actually if you look at it). I finally managed to get into contact with my thesis coordinator. While my topic is still Algorithmic Awareness, my focus has shifted a bit. Instead of looking at the consumer side, I’ll turn towards the producer-side. I’m taking a look at how news producers think about the algorithms behind Facebook and how they try to circumvent it. The central theoretical framework in this will be gatekeeping-theory, whereby personalisation through Facebook can be seen as a second gatekeeper above the news organisations. The bulk of my literature review still remains the same since I’m still talking about personalisation on the web, how Facebook works, the filter bubble and Algorithmic Awareness. The only difference is that in my last part I’ll be focusing on the producer side instead of on the consumer side.
So from all the things I talked about during my presentation on Thursday, a few things have fundamentally shifted. For that reason I’m actually not going to upload it, since I feel it does not represent the structure nor goal of my thesis well enough anymore
Read Nicholas’ readings about the silent majority and found them interesting!
It was fun to get an analyst’s view of how to reach this silent majority, for example, by
having anonymous surveys when dealing with subjects you’d rather not be too public about. I think that generally the term “Silent Majority” has a somewhat bad rep in this da and age, probably stemming from Trump supporters claiming the term by saying that “The Silent Majority stands with Trump” over and over, often putting this on signs at protests or posting about it on social media….Which is a bit ironic.
I’ve generally thought of the term as a way of saying that you, for example, disagree with current immigration laws etc. but don’t want to be vocal about it because of the backlash that often follows from, in my opinion, sane people.
So bearing this in mind, Nicholas’ readings showed me that from a data mining/analytical perspective the Silent Majority can be anything related to people “lurking” and not necessarily engaging in the same manner as the more vocal participants of, say, a message board.
On old message boards, before Reddit pretty much decimated them, you could always see how many people were on right now as “lurkers” or logged in, which I think maybe helped you to get a picture of how vast the Silent Majority was.
Maybe something like that should be implemented on Facebook etc? So that whenever you’re browsing a comment field you could get an estimate of how many people were lurking and how many people were contributing. I’m sure Facebook already has algorithms for this, I mean, this is the kind of thing they earn money from, but it would be nice, I think, for vocal contributors to see that people are reading their comments so that the contributors don’t feel that they’re “shouting into nothing”, so to speak. It could prevent the growing tide of disenchantment with online discussion that I feel is growing–of course, it could just make it worse.