  Research on infodemics, i.e., the rapid spread of (mis)information related to
a hazardous event, such as the COVID-19 pandemic, requires the integration of a
multiplicity of scientific disciplines. The dynamics emerging from infodemics
have the potential to generate complex behavioral patterns. In order to react
appropriately, it is of ultimate importance for the fields of Business and
Economics to understand the dynamics emerging from it. In the short run,
dynamics might lead to an adaptation in household spending or to a shift in
buying behavior towards online providers. In the long run, changes in
investments, consumer behavior, and markets are to be expected. We argue that
the dynamics emerge from complex interactions among multiple factors, such as
information and misinformation accessible for individuals and the formation and
revision of beliefs. (Mis)information accessible to individuals is, amongst
others, affected by algorithms specifically designed to provide personalized
information, while automated fact-checking algorithms can help reduce the
amount of circulating misinformation. The formation and revision of individual
(and probably false) beliefs and individual fact-checking and interpretation of
information are heavily affected by linguistic patterns inherent to information
during pandemics and infodemics and further factors, such as affect, intuition
and motives. We argue that, in order to get a deep(er) understanding of the
dynamics emerging from infodemics, the fields of Business and Economics should
integrate the perspectives of Computer Science and Information Systems,
(Computational) Linguistics, and Cognitive Science into the wider context of
economic systems (e.g., organizations, markets or industries) and propose a way
to do so.
