The Observatory on Social Media at Indiana University Studies the Parasitic/Symbiotic Interactions Between the Memes and Software

In Some Thoughts on the Netflix Documentary The Social Dilemma, The Perils of Software Enhanced Confirmation Bias and The Current Global Coevolution of COVID-19 RNA, Human DNA, Memes and Software we discussed the very complex nature of the ongoing parasitic/symbiotic relationships between the memes and social media software. Recall that softwarephysics maintains that software is the fifth wave of self-replicating information to sweep across the planet and is rapidly becoming the dominant form of self-replicating information on the Earth as it displaces the memes as the dominant form of self-replicating information on the planet.

The December 2020 issue of Scientific American features an article The Attention Economy by Filippo Menczer and Thomas Hills that discusses some of these parasitic/symbiotic relationships, especially as they relate to the spread of false memes by social media software. In that very interesting article, I learned about the Observatory on Social Media (OSoMe, pronounced 'awe•some') at Indiana University that is headed by Professor Filippo Menczer. Here is their website:

Observatory on Social Media
http://osome.iuni.iu.edu/

This website features the scientific work of a truly unique group of individuals in academia. The Observatory on Social Media is the only academic research group that I know of that is actively exploring the parasitic/symbiotic relationships between the memes and software and how these interactions are impacting the "real world" of human affairs. Much of the material gathered by the Observatory on Social Media stems from the Networks & agents Network (NaN) research group at Indiana University.

Networks & agents Network (NaN):
https://cnets.indiana.edu/groups/nan/

The NaN research group conducts many studies into the nature of the social networks created by social media software using large amounts of field data gathered in the wild by staff fieldwork and also by using numerous numerical models to conduct simulations of what is observed in the field. One of their chief areas of research is the spread of misinformation on the Internet via social media software. NaN has created a number of software tools that are available to the public to analyze such traffic models. The NaN website also features a large number of YouTube lectures that explain the work that they are doing. This webpage takes a bit of time to load so please be patient.

NaN talks and other videos:
https://cnets.indiana.edu/groups/nan/talks/

A good lecture to start with is one by Professor Filippo Menczer:

4 Reasons Why Social Media Make Us Vulnerable to Manipulation
https://www.youtube.com/watch?v=uLYbkTQT064

Professor Filippo Menczer is very interested in why misinformation seems to go viral just as often as true information in social media diffusion networks. The NaN research group has discovered a number of explanations for this. First, their models show that whenever a social network of trusted agents, composed of agents with a finite level of attention, is exposed to high levels of information overload, the misinformation memes tend to go viral more often than true memes. On the other hand, when the same network is exposed to lower levels of information overload, the true memes tend to propagate. Another cause for the spread of misinformation stems from the algorithmic bias that most social media websites employ. Because the purpose of their Machine Learning algorithms is to keep users engaged so that they see more ads, these algorithms naturally select for content that is more popular to accomplish that goal. Unfortunately, users then begin to equate popularity with quality because all they see is popular content. And because the social media Machine Learning algorithms soon learn the social biases of users, they also tend to channel users to similar content that reaffirms their worldview by means of confirmation bias. This causes polarization. Memes tend to spread very quickly within one echo chamber but not between echo chambers so debunking memes never confront misinformation memes. See Some Thoughts on the Netflix Documentary The Social Dilemma, The Perils of Software Enhanced Confirmation Bias and The Current Global Coevolution of COVID-19 RNA, Human DNA, Memes and Software for more on that. Novel memes also spread much easier than less dramatic memes. Misinformation memes also tend to be more sensational and with higher levels of novelty than more mundane true memes, and this also fosters the propagation of misinformation memes. Finally, programmed bots can become superspreaders of misinformation by being programmed to retweet misinformation. Observed field data indicate that bots are very effective at igniting the kindling of a viral cascade that later gets amplified by real human users into a misinformation bonfire.

Once again, let me repeat the fundamental characteristics of self-replicating information for those of you new to softwarephysics.

Self-Replicating Information – Information that persists through time by making copies of itself or by enlisting the support of other things to ensure that copies of itself are made.

The Characteristics of Self-Replicating Information
All forms of self-replicating information have some common characteristics:

1. All self-replicating information evolves over time through the Darwinian processes of inheritance, innovation and natural selection, which endows self-replicating information with one telling characteristic – the ability to survive in a Universe dominated by the second law of thermodynamics and nonlinearity.

2. All self-replicating information begins spontaneously as a parasitic mutation that obtains energy, information and sometimes matter from a host.

3. With time, the parasitic self-replicating information takes on a symbiotic relationship with its host.

4. Eventually, the self-replicating information becomes one with its host through the symbiotic integration of the host and the self-replicating information.

5. Ultimately, the self-replicating information replaces its host as the dominant form of self-replicating information.

6. Most hosts are also forms of self-replicating information.

7. All self-replicating information has to be a little bit nasty in order to survive.

8. The defining characteristic of self-replicating information is the ability of self-replicating information to change the boundary conditions of its utility phase space in new and unpredictable ways by means of exapting current functions into new uses that change the size and shape of its particular utility phase space. See Enablement - the Definitive Characteristic of Living Things for more on this last characteristic. That posting discusses Stuart Kauffman's theory of Enablement in which living things are seen to exapt existing functions into new and unpredictable functions by discovering the “AdjacentPossible” of springloaded preadaptations.

Over the past 4.56 billion years we have seen five waves of self-replicating information sweep across the surface of the Earth and totally rework the planet, as each new wave came to dominate the Earth:

1. Self-replicating autocatalytic metabolic pathways of organic molecules
2. RNA
3. DNA
4. Memes
5. Software

Software is currently the most recent wave of self-replicating information to arrive upon the scene and is rapidly becoming the dominant form of self-replicating information on the planet. For more on the above see A Brief History of Self-Replicating Information. Recently, the memes and software have formed a very powerful newly-formed parasitic/symbiotic relationship with the rise of social media software. In that parasitic/symbiotic relationship, the memes are now mainly being spread by means of social media software and social media software is being spread and financed by means of the memes. But again, this is nothing new. All 5 waves of self-replicating information are all coevolving by means of eternal parasitic/symbiotic relationships. For more on that see The Current Global Coevolution of COVID-19 RNA, Human DNA, Memes and Software.

Again, self-replicating information cannot think, so it cannot participate in a conspiracy-theory-like fashion to take over the world. All forms of self-replicating information are simply forms of mindless information responding to the blind Darwinian forces of inheritance, innovation and natural selection. Yet despite that, as each new wave of self-replicating information came to predominance over the past four billion years, they all managed to completely transform the surface of the entire planet, so we should not expect anything less from software as it comes to replace the memes as the dominant form of self-replicating information on the planet. But this time might be different. What might happen if software does eventually develop a Mind of its own? After all, that does seem to be the ultimate goal of all the current AI software research that is going on.

Conclusion
If you are at all interested in the parasitic/symbiotic relationships between the memes and social media software, you should definitely explore the above website of the Observatory on Social Media. The Observatory on Social Media seems to have really gotten started around 2016, so it is a rather new research effort that certainly should be heavily funded in today's hyperpolitical world because it is studying things like the transmission of misinformation on the Internet. In the modern political world, such matters are certainly as significant and as grave as the spread of nuclear weapons' secrets in the 1950s amongst the world powers.

Additionally, I think that the studies of social media networks by the Observatory on Social Media and NaN have a further application to many additional fields as well. If you think of the self-organizing coordinated networks of humans and bots that form the self-sustaining echo chambers that have been discovered in the wild as active agent-based meme-complexes, you have a form of self-replicating information with many of the characteristics of carbon-based life. In addition, and most importantly, they have done a great deal of fieldwork and collected tons of data in the wild. I bet that many researchers working on evolutionary biology, the origin of carbon-based life on the Earth, astrobiology and those working on the rise of eusocial behavior in species by means of multilevel selection would find their work extremely interesting and beneficial.

Their work could also help to revive memetics in academia. A few years back, I had a lengthy email exchange with Susan Blackmore, one of the founders of memetics, about her brilliant TED presentation which can be viewed at:

Memes and "temes"
https://www.ted.com/talks/susan_blackmore_on_memes_and_temes

Note that I consider Susan Blackmore's temes to really be technological artifacts that contain software. After all, a smartphone without software is simply a flake tool with a very dull edge. Susan Blackmore's most significant contribution is her hypothesis that the very large and highly over-engineered human brain evolved to store and process memes. Memetic-drive then went on to develop languages, cultures and social media software to further store and propagate memes. That is why we are such suckers for false memes. Our Minds evolved to store and propagate memes, even memes that are not acting in our best interests. For more on that see A Brief History of Self-Replicating Information.

Comments are welcome at scj333@sbcglobal.net

To see all posts on softwarephysics in reverse order go to:
https://softwarephysics.blogspot.com/

Regards,
Steve Johnston