Quantify Blogging Impact Factors
Blogging has become so popular nowadays.
Blogging existed in a different form before Internet services were available. The print newspapers used to have blogging columns by eminent reporters and writers.
Blogging became popular only after the Internet reached every home.
The world had many expert bloggers even before the crypto blogging platforms started to exist. When did you first start writing your blogs? I started to write blogs only in 2014 when LinkedIn opened its blogging platform "Pulse" for all its members.
We write blogs and eagerly wait to receive upvotes and tips. Do we bother to explore the engagement our blogs attracted? The blogging platform show displays of readers' engagement on the blogs.
Do you look only at the upvotes and tips of BCH? Do you also try to assess the level of engagement your blogs generate? Don't you wish to carry out simple arithmetic calculations to study the impact of your blog articles?
This is a technical article or a small research paper on assessing a published blog article using the publicly available status of engagement and earning data and quantifying it in terms of some Blogging Impact Factors (BIF).
People publish about their blogging journey
Some bloggers bother to assess their online writing journeys every month and year. They like to post their monthly earning report. Most of the reports contain tabular details of their public data about earnings, views, comments, etc.
I am happy to read these monthly and annual assessment reports detailing mostly public data. Some bloggers go a step further and disclose how much dollars they spend for "boosting" each article.
Recently, I read an article where a fellow writer (@Meyzee) displayed graphical plots of earnings. I like graphical plots because I am from the STEM (science, technology, engineering, mathematics) field. We are used to representing data in different forms of plots. That article indirectly inspired me to formulate some impact factors to assess any published blog.
Graphics: GIF created using title text and a Photo by Anete Lūsiņa on Unsplash.
I design some Blogging Impact Factors (BIF) for assessing a blog
I understand that most bloggers are not from science streams. So, they are not accustomed to creating graphical plots, although the cryptocurrency user community like graphical plots of price caps of different cryptocurrencies.
In this article, I define some Blogging Impact Factors (BIF) using simple arithmetic formulas. BIF can be used as an analytical tool to assess the engagement of blog articles on ReadCash, and other platforms. You need to utilize the publicly available status data of any blog post.
Since the status of blogs represents data, the impact of a blog can be quantified. Status information of blogs which are publicly available are:
Number of Views [NoV]
Number of Likes [NoL]
Number of Comments (comments + replies) [NoC]
Tips of Readers [ToR]
Tips of the Platform (rewarded bot) [ToP]
Total tips from All sources [ToA]
The number of shares could have been an interesting parameter. But, our parent platform doesn't have any register to record and display that information. LinkedIn and some other platforms display the number of shares which are private data, and are available only to the authors.
Let us define the following impact factors involving the information parameters available in the article status described above.
Graphics: Image containing formulas for calculating Blogging Impact Factors (BIF).
Creator and copyright: Unity (Debesh Choudhury).
The Blogging Impact Factors can be calculated for any published article on ReadCash and any other online blogging platforms. To calculate BIFs, the engagement data have to be available publicly to any viewers.
Examples of "Blogging Impact Factors" of some blog articles
Without much ado, let me show a few examples of the impacts of some randomly selected articles by fellow bloggers and me. I take the liberty to use two articles by two fellow bloggers.
"I've got my early Birthday present!"
https://read.cash/@Meyzee/ive-got-my-early-birthday-present-d3f611c4
NoV = 52
NoL = 21
NoC = 34
ToR = $0.58
ToP = $21.28
ToA = $21.86
Engagement Impact Factor = (NoL + NoC)/NoV = (21+34)/52 = 1.06
Reader Impact Factor = T0R/ToA = 0.58/21.86 = 0.03
Platform Impact Factor = ToP/ToA = 21.28/21.86 = 0.97
==============
"If You Are Worth Anything Then You Are Contagious"
https://read.cash/@Talecharm/if-you-are-worth-anything-then-you-are-contagious-49595124
NoV = 83
NoL = 30
NoC = 30
ToR = $0.63
ToP = $11.21
ToA = $11.84
Engagement Impact Factor = (NoL + NoC)/NoV = (30+30)/83 = 0.72
Reader Impact Factor = T0R/ToA = 0.63/11.84 = 0.05
Platform Impact Factor = ToP/ToA = 11.21/11.84 = 0.95
==============
"Time Currency"
https://read.cash/@Unity/time-currency-a3f1cdeb
NoV = 79
NoL = 13
NoC = 10
ToR = $0.58
ToP = $11.02
ToA = $11.60
Engagement Impact Factor = (NoL + NoC)/NoV = (13+10)/79 = 0.29
Reader Impact Factor = T0R/ToA = 00.58/11.60 = 0.05
Platform Impact Factor = ToP/ToA = 11.02/11.60 = 0.95
==============
I could have taken more examples. But, for the time being, I keep it only three examples, one article each by @Meyzee, @Talecharm and by @Unity (myself).
Closing remarks
I needed some impact factors for assessing blog articles published on ReadCash.
I have created three impact factors: Engagement Impact Factor, Reader Impact Factor, and Platform Impact Factor.
The arithmetic formulas of the Blogging Impact Factors are simple ratios of data numbers/earnings and unitless numbers.
It utilizes the publicly available engagement and earning data of published blogs.
If it so happens that both the numerator and denominator of the ratio formulas are zero, the arithmetic results will be undefined and may be set as nil impact.
Divisible by zero condition exists in a sub-topic of mathematics called calculus. The undefined state may take an infinitely large value when the denominator is vanishingly small, i.e., tends to zero.
It is the first trial of defining a set of Blogging Impact Factors. There could be errors in conceptualizing the newly proposed assessing impact factors.
I have defined the parameters and created the Blogging Impact Factors' formulas, so it is my own formula. There is a lot of scopes to develop it further.
Feedback from the blogging community is very much needed to improve the definitions of the Blogging Impact Factors.
About me
I am from Science, Technology, Engineering, and Mathematics (STEM) field. I have also added "Arts" and "Fine Art" to my interests and made my current interests STEAM - Science, Technology, Engineering, Arts, and Mathematics.
I develop password security and cybersecurity solutions relevant to cryptocurrencies, blockchain, and other block-less distributed ledgers.
Thanks to all my sponsors, whose names appear in the "Sponsor" pannel.
I hope that the entire blogging community will strive here and elsewhere.
If you have a little time, consider to explore my "Learning Times" and other channels on Odysee-dot-Com and earn crypto coin LBRY Credit or LBC for consuming and creating content.
Cheers!
Unity (Debesh Choudhury)
Text Copyright © 2022 Debesh Choudhury — All Rights Reserved
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Lead Image: GIF created using title text and a Photo by Anete Lūsiņa on Unsplash.
All other graphics and videos are credited just below it.
Disclaimer: All texts are mine and original. Any similarity and resemblance to any other content are purely accidental. The article is not advice for life, career, business, or investment. Do your research before adopting any options.
Unite and Empower Humanity.
April 13, 2022.
Very interesting formula presented sir. I'm gonna study this after my vacation! But comparing to other BIF, if you'll look at it, it is not about views but the engagement. Or maybe the topic also plays a big factor.