  Online social media, such as Twitter and Instagram, democratized information
broadcast, allowing anyone to share information about themselves and their
surroundings at an unprecedented scale. The large volume of information thus
posted on these media offer a new lens into the physical world through the eyes
of the social network. The exploitation of this lens to inspect aspects of
world state has recently been termed social sensing. The power of manipulating
reality via the use (or intentional misuse) of social media opened concerns
with issues ranging from radicalization by terror propaganda to potential
manipulation of elections in mature democracies. Many important challenges and
open research questions arise in this emerging field that aims to better
understand how information can be extracted from the medium and what properties
characterize the extracted information and the world it represents. Addressing
the above challenges requires multi-disciplinary research at the intersection
of computer science and social sciences that combines cyber-physical computing,
sociology, sensor networks, social networks, cognition, data mining, estimation
theory, data fusion, information theory, linguistics, machine learning,
behavioral economics, and possibly others. This paper surveys important
directions in social sensing, identifies current research challenges, and
outlines avenues for future research.
