An Empirical Study on the Relationship between the Followers' Number and Influence of Microblogging
Rui Wang, Yongsheng Jin
Abstract
Rui Wang, Yongsheng Jin
Abstract
With the emergence of microbloggling in China, how to expand enterprise influence by microblogging marketing has been becoming a hot topic. According to AISAS theory (Attention, Interest, Search, Action, Share), this paper establishes an AR(1) model (first-order auto-regressive model) describing the relationship between the followers' number and influence of microblogging. With data acquired from the first typical enterprise marketing case on Sina Microblog, this paper verifies the rationality of the AR(1) model by empirical analysis. Based on the obtained results, this paper makes reasonable proposals for improving enterprise influence through microblogging marketing.
OpenAlex reports 15 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
With the emergence of microbloggling in China, how to expand enterprise influence by microblogging marketing has been becoming a hot topic. According to AISAS theory (Attention, Interest, Search, Action, Share), this paper establishes an AR(1) model (first-order auto-regressive model) describing the relationship between the followers' number and influence of microblogging. With data acquired from the first typical enterprise marketing case on Sina Microblog, this paper verifies the rationality of the AR(1) model by empirical analysis. Based on the obtained results, this paper makes reasonable proposals for improving enterprise influence through microblogging marketing.
Key concepts: Microblogging, Social media, Computer science, Empirical research, Rationality, Order (exchange), Action (physics), Data science