  Social media has changed the landscape of marketing and consumer research as
the adoption and promotion of businesses is becoming more and more dependent on
how the customers are interacting and feeling about the business on platforms
like Facebook, Twitter, Yelp etc. Social review websites like Yelp have become
an important source of information about different businesses. Social influence
on these online platforms can result in individuals adopting or promoting ideas
and actions resulting in information cascades. Research on information cascades
have been gaining popularity over the last few years but most of the research
has been focused on platforms like Twitter and Facebook. Research on the
adoption or promotion of product using cascades can help determine important
latent patterns of social influence.
  In this work, we have analyzed the spread of information i.e. cascades in
Yelp across different cities in Europe and North America. We have enumerated
and analyzed different cascade topologies that occur in the Yelp social
networks. Some of our significant findings include the presence of a
significant number of cascades in Yelp reviews indicating the importance of
social influence, heavy-tailed distribution of cascades and possibility to
accurately predict the size of cascades on the basis of initial reviews. In
addition, we have also found that the characteristics of the non-root nodes and
the non-root reviews are much more important type of feature as compared to the
properties of the root nodes and root reviews of the cascade.
  These findings can help social scientists to analyze customer behavior across
different cities in a much more systematic way. Furthermore, it can also help
the businesses in a city to figure out different consumer trends and hence
improve their processes and offerings.
