I see the point in a model being "predictive" (post-dictive) but also I think all models should take into consideration all the other post-dicitve and predictive models. There is a good body of evidence validating Metcalfe on communication-networks like:

Facebook und Tencent: Zhang et al. 2015
Bitcoin, Ethereum, Dash Alabi 2017
Bitcoin: Peterson 2018, Civitarese 2018

Sarnoffs Function V = a × n a: USD/MAU
Reeds Function V = a × (2^(n) − 1) a: USD/MAU
Odlyzkos Function V = a × n log(n) a: USD/MAU
Metcalfes Function V = a × n² a: USD/MAU²

[Cermak 2017]

and it filters the network-value by use. There are times when Bitcoin follows Metcalfe, which is dependent on the number of monthly active users (MAU) (n log(n)), but there are also times when the dynamic is driven by speculation. And this goes so far that bubbles and bottoms become somehow predictable (Sornette et al. 2018 - Are Bitcoin Bubbles Predictable? Combining a Generalized Metcalfe's Law and the LPPLS Model). This is in line with the phenomenon, that in a retail-driven market, the public interest and gossip on social-media was in hindsight "predictive" for bitcoins price.

Evidence for Social-Media being predictive:

(Lui und Tsyvinki 2018): Risks and Returns of Cryptocurrency
(Phillips und Gorse 2018):Cryptocurrency price drivers: Wavelet coherence analysis revisited
(ElBahrawi et al. 2017): Evolutionary dynamics of the cryptocurrency market
(Wang und Vernge 2017): Buzz Factor or Innovation Potential: What Explains Cryptocurrencies’ Returns?
(Kim et al. 2016): Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies
(Kristoufek 2015): What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis
(Garcia et al. 2014): The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy
(Matta et al. 2015): Bitcoin Spread Prediction Using Social And Web
Search Media
(Garcia und Schweizer 2015):Social signals and algorithmic trading of Bitcoin
(related Studies)

Now you come with a new model which says: underlying all of this, there is the self-fullfilling narrative of a store of value. how does this fit the narrative?