Abstract— The advance of social computing study is grim n very fast to the extent influenced in many aspects of our daily life. One of those aspects is application marl:cling and advertising. Business are always demand the , :Teeth e "ay to understand their market, but the absent of poi' erful mrt ries has cause some problem. The availability Big Data ail around us has triggered a new perspective on how we approach those problems. Online social network disseminate information much faster than before, supporting highly exposure of brand a Wa! mess. The network behavior of the information spreading can lie explained by the study of complex network.
In this paper, we propose the social network modelling. approach using graph theory to understami on ho'% brand information travels in online social network god hil%1 it en n benrlit for business. In prior study m ma ci.eting. it is uncommon to approach phenomenon using sori.,i seta,,; :. model and online social data, they arc mostly using :I I: eat ion n a from population sample. Our paper will enrich effort in mi,cketing study. Our experiment use conversation data from Intl,mcsian Twitter user contains specific brand keyword
Keywords—social computing: social network analysis: graph theory; brand awareness: marketing; Twitter: complex network; Big Data