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Could we use a scoring system for digital content, assigning them an ‘online (digital) fitness’?

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Subash Chapagain
Subash Chapagain Oct 21, 2020
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Given that all forms of digital content are memes of one kind or another, can we employ a scoring matrix that determines the value of online ideas over time?



So, a little bit of background first:
We all have used, laughed at, made, and shared memes. But do we actually know what the real concept underlying the meme is?
A Meme is more than a viral joke on the internet. It is an idea much more complex than a mere string of characters on top of a picture. To put it in context, memes in society/platform are what genes in a living system are. In saying so, I would have to elaborate on how this analogy is justified.

The idea of a meme appeared for the first time in the book titled “The Selfish Gene” by Professor Richard Dawkins, a biologist and a vocal proponent of scientific and rationalist thinking. To borrow his words first hand, a MEME is a cultural equivalent of a gene. If you have known basic biology, you might very well recall that a gene is a unit, a section of chromosome (or a DNA molecule) that can transmit to the next generation via a biological reproduction process. And since genes are responsible for encoding proteins (and biomolecules like RNA) that make up any living organism, they are the ultimate determinant of the evolution of species. This is a purely Darwinian concept, and it has to be also understood that occasional errors in the biological copying of these genes during reproduction is the basis of evolution that on a larger historical time frame can give rise to organisms with new, peculiar features, eventually giving rise to species anew as well.

Imitation is what gives memes their intrinsic virtue. When Richard Dawkins proposed the meme theory, this was exactly what he wanted to put forward. The choice of the word itself proves his intention in light- ‘Mimeme’ is a Greek word that translates to imitation, and Dawkins ingeniously coined the term ‘meme’ to reflect the essence of the phenomenon. Just as the process of biological replication of genes (DNA to be precise) is intrinsically accompanied by errors, the imitation of memes is also erroneous, and hence responsible for bringing about new variations in the original idea (or meme). The field of linguistics can offer a plausible example for explicating this case: the rise of new dialects, new forms of language, new words, and catch-phrases are the result of a slight error in imitations.

It is an established axiom in biology that that evolution is the result of copying errors during reproduction. This brings us to yet another concept in biology: evolutionary fitness. Evolutionary fitness can be conceptually understood as the ability of an organism (at the macro level) and that of a gene (at the micro-level) to survive and reproduce in the environment in which they are. Hence, analyzing fitness in terms of its mathematical measures, it can be considered as a measure of viability: how long can a gene (and hence the species that has it) continue to exist in the environment it finds itself in? The more it survives, the more fit (evolutionarily) it is!



Since ideas online are also constantly evolving over time-being copied, shared, strengthened, weakened, imitated, and omitted- I imagine it shall somehow be possible to develop a system (AI assisted) to assign a relative value to the digital contents. This value can be called the ‘online/digital fitness of a meme’- meme being any content/idea/concept that is present online. To build upon the meme: gene analogy of Professor Dawkins, can we devise an analogous concept of fitness for memes as biologists do with fitness for genes? (For example, myspace.com could be deemed to have less fitness now, as compared to Spotify; ditto for Hi5.com vs Facebook.) At a more basic level, can we distill this idea to unitary contents like a post, a photo, video, or an audio file? What do you think would be the utility of such a scoring scheme?

[1]Orr HA. Fitness and its role in evolutionary genetics. Nat Rev Genet. 2009;10(8):531-539. doi:10.1038/nrg2603

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Shubhankar Kulkarni
Shubhankar Kulkarnia year ago
This seems like a good idea. I am thinking about its use. How can we use the fitness of a meme? We know a meme is thriving since the majority of the people know about it. So spreading the best memes cannot be one of the uses. The second use I could think of was monetizing the memes. The one coming up with the best meme gets some prize, every retweet/ share of the meme gives the owner some share of the income generated. But, that too, is in place. Knowing the fitness of a meme would not bring a radical change in that.

Here are some points that form the opposite view. Memes are short-lives when compared to genes. Knowing genes better, therefore, makes more sense than studying memes. Another reason why the fitness of a meme might not help much is that fitness is determined based on the spread of a meme and it is only known once the meme has spread.

This leads us to one use of the fitness of the memes - to identify a pattern and then predict the fitness, and therefore, the spread of new memes. The pains of predicting the fitness will only be justified if the fitness is put to better use.
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Subash Chapagain
Subash Chapagaina year ago
Shubhankar Kulkarni
I was thinking that if there was a way to figure out what type of contents online tend to be more fit, maybe we could then use the scoring system to re-enforce positive contents vs the negative ones. That is why I stressed on considering every content (be it a post, audio, a video or any other format) as a meme. Taken from the fundamental definition of a meme, this is indeed the case. Since every content on its own is an idea (or a proxy of an idea), it could be taken as a meme. I am trying to establish a meme-centric view of the digital world, analogous to the gene-centric view of the biological world.

This approach could be particularly useful in tackling fake news and mis-information, if established and updated accordingly.
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Shubhankar Kulkarni
Shubhankar Kulkarnia year ago
Subash Chapagain I understand. A separate problem that arises here is to define a positive and a negaitive meme. There is a lot of grey area there. Also, positive and negative memes are context-dependent, not universal. I can't get my head around how scoring can tackle fake news and mis-information.
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Subash Chapagain
Subash Chapagaina year ago
Shubhankar Kulkarni
To distinguish fake news or wrong information beforehand might be difficult, however, in the retrospect, I believe there already are existing algorithms that allow us to do so. By using the same approach that allows twitter or facebook to flag graphic content (hence giving these contents a low score), we could train the deep learning system (there already are deepfake algorithms that can meta-learn in a rapid scale) to detect the low scoring contents and notify the moderators of the respective platforms.

Another offshoot may be futuristic use of such a scoring system is to associate each individual's 'digital persona' with a value derived from the cumulative scores of the contents he/she generates, and using that value as some kind of currency online. However, a lot of variables need to be adjusted for that. I was thinking of creating an idea session around this concept. I am still mapping my mind as to how such a currency might be developed and regulated.
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Shubhankar Kulkarni
Shubhankar Kulkarnia year ago
Subash Chapagain If you evaluate the sincerity of a meme in retrospect, the damage is already done, the meme will have already reached the majority of people. We might need a different approach here.

I agree with your second paragraph. We can attach a digital score for users just like all other social networking sites do (followers, likes, etc.). We need to figure out what additional information can be derived from the "digital persona" that the current criteria for evaluation (followers, likes, etc.) don't provide.
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