Talita Greyling (p)

Ana Tubadji

COVID-19 has had a significant impact on how we interact with others, go about our lives, work, study and many other aspects. Unfortunately, COVID-19 continues to wreak havoc globally with over 5 million people having lost their lives despite collective best efforts. Research shows that receiving the COVID-19 vaccine is the best way to protect yourself, your loved ones and your community against contracting the virus. However, vaccination rates in the Western world are slowing down, and there is a sense of increased complacency. We now know that negative emotions such as fear influences peoples’ positive attitudes towards the COVID-19 vaccine. We also know that happier people make better health-related decisions. To better understand the trend in vaccination rates, we investigate the relationship between a nation’s subjective well-being, measured by happiness, and COVID-19 vaccination rates for ten countries in the Northern and Southern hemispheres. To measure happiness, we use the Gross National Happiness index (GNH), derived from Big Data and from the Our World In Data; we use the vaccination rate. We consistently find a positive relationship in that higher levels of happiness encourage higher vaccination rates. In terms of policy, the government should offer people help with the central problems in their lives. Surely, the costs of improvements in social and psychological infrastructure are small compared with physical infrastructure costs. And the subsequent benefit to society at large could just possibly be winning the battle against COVID-19.

Frederic Boy (p)

Talita Greyling

In the current global environment, digital technologies mediate our relationships and experiences. People rely on digital services and devices to consume, communicate, be informed, and be entertained. Finely grained insights from the interplay between technologies and people’s psychological, social, economic, political, and cultural digital lives are essential to understanding contemporary society. When equipped with cross-disciplinary knowledge, at the intersection of Social & Behavioural Sciences and Artificial Intelligence, researchers and practitioners will be better able to map connections between segments of our digital lives. There is an urgent need to translate the computational methods of analysis from data science and epidemiology to fields in the social sciences. The unfolding of the COVID-19 outbreak was an unprecedented and unanticipated opportunity to understand how sudden global shocks modulate people’s online searches when seeking information about their emotional well-being.
The present paper explores multiple validations of a novel general Machine Learning framework designed to investigate how highly granular can augment social and media listening and population-scale well-being surveys.
I will first present how we uncovered and validated strong linkages between time-series in the digital surveillance of search engines during the pandemic and 1- a selection of social media feeds in the UK, Spain and the USA, and 2- large scale well-being surveys in the United Kingdom and Wales. Then I will show how high-frequency search-listening web analytics (sampled every 8-minutes) provide robust, finely grained, and replicable evidence on variation in aggregated mental health measures at the population level. Finally, I will review the evidence we gathered in international search-listening research that analysed the relationship between online search behaviour and an individual’s immediate need for knowledge in Romania, France, Turkey, Italy, Germany, and the United Kingdom.
Results are discussed against the backdrop of creating transparent surveillance systems of open-source data, an essential component of a healthy, democratic digital society.

Yuriy Gorodnichenko, Tho Pham, Oleksandr Talavera (p)

Frederic Boy

We develop a deep learning model to detect emotions embedded in press conferences after the meetings of the Federal Open Market Committee and examine
the influence of the detected emotions on financial markets. We find that, after controlling for the Fed’s actions and the sentiment in policy texts, positive tone in the voices of Fed Chairs leads to significant increases in share prices. Other financial variables also respond to vocal cues from the Chairs. Hence, how policy messages are communicated can move the financial market. Our results provide implications for improving the effectiveness of central bank communications.

Annie Tubadji (p), Pierpaolo Pattitoni

Oleksandr Talavera

Local culture (as the local programming of the mind) gets expressed in certain locally specific verbal behavior patterns – i.e. the local language. Our hypothesis is that these linguistic patterns, especially those passed through the verification of local institutions and appearing as printed language, can serve for predicting local economic growth over time. In his seminal work on skewed distribution functions, Herbert Simon (1955) noted that language and economic development both seem to be generated by a similar process. We suggest that this implies language and economic development might have a causal link which can be distinguished based on the temporal element in the process generation. We pose two main questions: (i) how does the programming of the mind through language behaves as a process over time – if language is itself a persistent, path-dependent or resilient process and (ii) what is the direction of the causal link (if any) between language and economic development. We use time series analysis (ARIMA, VECM and Granger causality) to analyze the Google Ngrams dataset representing a 4% sample of the world libraries. Our findings suggest that language and economic development exist largely in a dialectic relationship; the effect of economic processes over language is stronger in the long term, but language does have the power to change economic development in a particular moment in time. The DNA of language, carried in the innovations of language over time, suggests that the errors are indeed not normally distributed, i.e. we have the power to change our language and thus our economic reality but we very rarely use the power of our free will to try change out institutional context and structure and are mostly living in the economic reality determined by it.