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Created page with "== Title == Scheduling a Cascade with Opposing Influences == Speaker == Anshul Sawant, University of Maryland == Abstract == Adoption or rejection of ideas, products, and te..."
== Title ==
Scheduling a Cascade with Opposing Influences
== Speaker ==
Anshul Sawant, University of Maryland
== Abstract ==
Adoption or rejection of ideas, products, and technologies in a society is often governed by simultaneous propagation of positive and negative influences. Consider a planner trying to introduce an idea in different parts of a society at different times. How should the planner design a schedule considering this fact that positive reaction to the idea in early areas has a positive impact on probability of success in later areas, whereas a flopped reaction has exactly the opposite impact? We generalize a well-known economic model to study this situation, where the reaction of each area is determined by its initial preference and
the reaction of early areas. We model the society by a graph where each node represents an a group of people with same preferences. We consider a full propagation setting where news and influences propagate between every two areas. We generalize previous works by studying the problem when people in different areas have differing behaviours.
Scheduling a Cascade with Opposing Influences
== Speaker ==
Anshul Sawant, University of Maryland
== Abstract ==
Adoption or rejection of ideas, products, and technologies in a society is often governed by simultaneous propagation of positive and negative influences. Consider a planner trying to introduce an idea in different parts of a society at different times. How should the planner design a schedule considering this fact that positive reaction to the idea in early areas has a positive impact on probability of success in later areas, whereas a flopped reaction has exactly the opposite impact? We generalize a well-known economic model to study this situation, where the reaction of each area is determined by its initial preference and
the reaction of early areas. We model the society by a graph where each node represents an a group of people with same preferences. We consider a full propagation setting where news and influences propagate between every two areas. We generalize previous works by studying the problem when people in different areas have differing behaviours.
