The Power of Narratives

No one can deny that the way information is consumed today has changed dramatically during last 10 years. From Newspapers and TV to social networks. Narratives have always existed; stories are just the way humans reflect about facts and connect with others. However, in the last decade we’ve seen the boost of these narratives thanks to social network technology and developments around digital nudging [1].

Narratives and Epidemiology

Narratives are transmitted like viruses, following a similar pattern of how disease spreads. In fact, we can leverage as starting point Kermack-McKendrick SIR model for mathematical modelling. If you’re more interested on this topic you can read further the work done with modified SIR models like, Laijun Zhao [2] using news data, Christian Bauckhage SIRS model with memes [3] and Markov models with You Tube videos [4].

2013 Nobel economy awarded Robert J. Schiller in his great book 2019 Narrative Economics [5] also mentioned that narratives can come back again mutating for each new era. He explores different situations when there was a change of sentiment, from unions to rich people or from economic frugality to hedonism. These narratives have experimented revisions in the way were seen by society along the time.

Technological Narrative

As Robert J. Schiller confirms these revisions of the average sentiment of the story can be susceptive about the social context when they got viral again. One of the examples he mentions is how technological narrative has mutated from the positive labour-saving machinery from the 19th century to the technological unemployment during the Great Depression and again after the 2007-9 world financial crisis.

Alternative facts as a Narrative

Looking for the term “alternative facts” in books, we can reflect somehow about the timing of this new narrative.

But looking from news and media perspective (GDELT) we can see that it really exploded during beginning of 2017. Right after 2016 US elections with Trump. Actually, this phrase was used by US. Counsellor to the President Kellyanne Conway during a Meet the Press interview on January 22, 2017 where he was defining the White House Press Secretary Sean Spicer's false statement about the attendance numbers of Donald Trump's inauguration as President of the United States as “alternative facts”.

Alternative facts and the Stock Market

Trump not only decided to use social networks as the main channel of communication, but he has been broadcasting his thoughts in real time creating thousands of Tweets. This has enabled analysis and research about the impact of his narratives. From the impact on Fed’s monetary policy [6], or Bank of America Merrill Lynch report said that stocks tend to fall on days during which Trump tweets more than 35 times and rise on days when he tweets less than five times [7]. JPMorgan’s “Volfefe Index” tracks market movements in response to President Trumps tweets [8] found direct correlations with market movements.

Alternative facts and the challenge for democracy

During the Trump government a new term was also revisited “Fact Check”. Webs around the world popped up trying to fact-check social network data. For instance, as of today The Washington Post has identified during the 1455 days of Trump in the White House 30.529 false or misleading claims.

After the Capitol Assault, Google, Facebook and Tweeter decided to block Donald Trump account. Also, Amazon cancelled AWS service for Parler a popular conspiracy theory supporter microblogging service. Is evident that social networks have not been accountable for the nature of the news shared nor the continuous nudging applied to consumers, putting in risk society (I recommend for more info reading The Age of Surveillance Capitalism from the social psychologist Shoshana Zuboff [9]).

The Good News

As citizens we need to be more familiar with the principles of journalism to demand transparency. Applying the highest news standards to social media companies [10] but also with the scientific method, which is the ultimate way to validate o reject a statement.

Also, demanding to lawmaker’s the development of incentives/disincentives to push companies spreading truthful stories and regulating social nudging (maybe a tax to nudging?).

Last point, mathematical epidemiology is a mature field and concepts such as the basic reproduction number allow for estimating if a viral outbreak is imminent or what the final outbreak size will be. In fact, scientist during 2020 have been using and even improving these models to predict Covid-19 outbreak. Why not to leverage as a control mechanism for fake news spreading?

References

[1] Mirbabaie, M., Ehnis, C., Stieglitz, S. et al. (2020).

[2] Laijun Zhao et al. (2013)

[3] Bauckhage, Christian. "Insights into Internet Memes." (2011)

[4] Bauckhage, Christian, Fabian Hadiji, and Kristian Kersting. "How viral are viral videos?." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 9. No. 1. 2015.

[5] Narrative Economics: How Stories Go Viral and Drive Major Economic Events. Robert J. Shiller (2019)

[6] Bianchi, Francesco and Kind, Thilo and Kung, Howard, Threats to Central Bank Independence: High-Frequency Evidence with Twitter (September 15, 2019).

[7] The more Trump tweets, the worse it is for stocks, research finds (2019)

[8] Volfefe Index

[9] The Age of Surveillance Capitalism. Shoshana Zuboff (2019)

[10] The 10 Principles Journalism (American Press Association)