Effectiveness Of Opinion Influence Approaches In Highly Clustered Online Social Networks

A mathematical model was developed for opinion propagation on online social networks using a scale-free network with an adjustable clustering coefficient. Connected nodes influence each other when the difference between their opinion values is less than a threshold value. The model is used to examine effectiveness of three different approaches for influencing public opinion. The approaches examined include (1) a "Class", defined as an approach (such as a class or book) that greatly influences a small, randomly selected portion of the population, (2) an "Advertisement", defined as an approach (such as a TV or online advertisement) that has a small influence at each viewing on a large randomly selected portion of the population, and (3) an "App", defined as an approach (such as a Facebook game or smartphone "App") that spreads via the online social network (rather than randomly) and has a small influence at each viewing on the affected population. The Class and Advertisement approaches result in similar overall influence on the population, despite the fact that these approaches are highly different. In contrast, the App approach has a much more significant effect on opinion values of users occupying clusters within the social network compared to the overall population.