  Do today's communication technologies hold potential to alleviate poverty?
The mobile phone's accessibility and use allows us with an unprecedented volume
of data on social interactions, mobility and more. Can this data help us better
understand, characterize and alleviate poverty in one of the poorest nations in
the world. Our study is an attempt in this direction. We discuss two concepts,
which are both interconnected and immensely useful for securing the important
link between mobile accessibility and poverty.
  First, we use the cellular-communications data to construct virtual
connectivity maps for Senegal, which are then correlated with the poverty
indicators to learn a model. Our model predicts poverty index at any spatial
resolution. Thus, we generate Poverty Maps for Senegal at an unprecedented
finer resolution. Such maps are essential for understanding what characterizes
poverty in a certain region, and how it differentiates from other regions, for
targeted responses for the demographic of the population that is most needy. An
interesting fact, that is empirically proved by our methodology, is that a
large portion of all communication, and economic activity in Senegal is
concentrated in Dakar, leaving many other regions marginalized.
  Second, we study how user behavioral statistics, gathered from
cellular-communications, correlate with the poverty indicators. Can this
relationship be learnt as a model to generate poverty maps at a finer
resolution? Surprisingly, this relationship can give us an alternate poverty
map, that is solely based on the user behavior. Since poverty is a complex
phenomenon, poverty maps showcasing multiple perspectives, such as ours,
provide policymakers with better insights for effective responses for poverty
eradication.
