Just How Loud Do You Have to Scream to Be Heard on Twitter?

I’ve decided that I hate social media. I’ve joined neither Facebook nor Snap. I am on Instagram, but only to share vacation pictures with my family because I’m too lazy to sort and share photos with them after my trips. I gave up on LinkedIn because I find the timeline poorly designed and I’m not looking for a job anyway. I also stopped reading (and generally writing) blogs because I don’t care and don’t think other people do either. So, if someone besides the Director of Communication for bloomfield knoble is reading this, you have my permission to bail out now.

Well, if you’re actually still reading, then I have to admit that I used to really be into Twitter. I mean really into Twitter. I would post all day — use hashtags, join conversations, try to influence conversations (for or against depending on the topic) and more often than not, complain about some injustice against me (real or perceived). At one point I had nearly 100,000 followers.

And then a funny thing happened. I got bored. I’ve already shared with you that I’m quite lazy, so it didn’t take long for the novelty of Twitter to subside. I went from Tweeting a lot to now-and-then and then that became infrequently until it was pretty much never. I lost nearly all of my subscribers but honestly didn’t care. Most of my friends had given up on Twitter too – either also moving away from social networks in general or moving to a different platform. As such, I simply let it fade from memory and forgot about it.

Until recently, when I got really mad at my pest control company for a real (not perceived) injustice. I was so mad that I hopped on Twitter just to vent my frustration and (in my imaginary world) start a movement among the masses that had also been wronged by said company. Together our voices would force change as our postings became a trending topic which would go viral and then spread across different media and social networks. Satisfaction would be rendered. Justice would be mine!

Except, of course, none of that happened. No one joined the conversation – not one like or reply or retweet – not even from the brand itself as I’m not sure they even monitored their unverified account anyway.

I wasn’t surprised that my Tweets got no traction – I have few followers now – many of whom I suspect are inactive as well – and although I structured the posts properly (tagging the brand, using a hashtag) it’s just background noise in today’s world of political topic-driven social media. However, as a Behavioral Economist, I was interested in just what I would have to do to be heard on Twitter.

As an advertising agency, we at bloomfield knoble have been chasing the dream of going viral forever, but no amount of math or predictive analytics can really account for the irrationality of humans. Nevertheless, I was curious about how to measure – beyond the analytics Twitter provides – how one could analyze impact on a social network. A bit of research and some investigating later, I came across an excellent paper in the Journal of Physics by Natya Taniarza, Adiwijaya and Warih Maharani at the School of Computing, Telkom University, Bandung, Indonesia. Their paper, Social network analysis using k-Path centrality method, gave me some great insight into why my Tweets (in particular) don’t matter.

Here’s the abstract to their paper:

“k-Path centrality is deemed as one of the effective methods to be applied in centrality measurement in which the influential node is estimated as the node that is being passed by information path frequently. Regarding this, k-Path centrality has been employed in the analysis of this paper specifically by adapting random-algorithm approach in order to: (1) determine the influential user’s ranking in social media Twitter; and (2) ascertain the influence of parameter ain the numeration of k-Path centrality. According to the analysis, the findings showed that the method of k-Path centrality with random-algorithm approach can be used to determine user’s ranking which influences in the dissemination of information in Twitter. Furthermore, the findings also showed that parameter influenced the duration and the ranking results: the less the avalue, the longer the duration, yet the ranking results were more stable.”

The paper is worth reading and I’m not going to do justice to their research, but here’s the bottom-line – specifically as it impacts me. Basically, a person needs a lot of followers (which I don’t have anymore) or needs to wield influence in a group (node) of people who are likely to participate in the conversation – or are also connected in different groups where they wield influence.

It’s like the gossip game. If I have a small group of friends, but they have no friends, then even though I shared – our little circle is as far as it goes. However, if one of my friends is in another circle of friends – and that person tells that circle – and someone in that circle tells another circle – pretty soon a lot of people have heard. This is actually common-sense in a way. Anyone that has ever been on social media gets how this works. It’s not the process that can be hard to understand – it’s the measurement.

The big buzzword for the past couple of years has been “influencer marketing.” Brands know they need to have an influencer but understanding who – and how much to spend – and what the return-on-investment could be – is a vital part of marketing. Understanding that influence doesn’t move in a straight-line and utilizing the learning in Taniarza’s paper may be an important factor in projecting success.

Anyway, all the math showed me was that no one cared that I was whining about my pest control company, so I gave up on my dream of Twitter vengeance and decided to vent my frustration against their company by firing them – convinced that the $29 per month they were losing would cripple their business economy. Yeah, that’ll show ‘em! Who’s with me?



Taniarza N., Maharani A., Maharani W. Social network analysis using k-Path centrality method. IOP Publishing: International Conference on Data and Information Science. IOP Conf. Series: Journal of Physics: Conf. Series 971 (2018) 012015. dos: 10.1088/1742-6596/971/1/012015. (Natya Taniarza et al 2018 J. Phys.: Conf. Ser 971 012015)