Analysis and empirical study on influence factors of enterprise microblog marketing effect

The article applies the diffusion status of “repost information cascade” to measure the marketing effect of enterprise Microblog. Integrating social network information diffusion and dissemination dynamics theory, the author selects variables from three aspects of Microblog characteristics, enterprise node characteristics, repost node heterogeneity as influence factors to build the influence factor model of information cascade diffusion effect and verify the model assumption on the basis of the actual data collected in Sina Microblog. The study finds that both Microblog additional information and enterprise node characteristics have significant influence on the accumulated Microblog repost number; acceptance-type Hub node has more significant influence on information diffusion speed, while diffusion-type Hub nodes can help extend the information dissemination scale. Key Words—enterprise Microblog, Microblog marketing, information cascade, social network, information dissemination. _____________________________________________________________________________________________ INTRODUCTION “Microblog marketing” refers to the Internet marketing behavior that enterprises or organizations take Microblog as a medium and conduct information dissemination, sharing and interaction. The studies on Microblog marketing in macro perspective mainly explore the Microblog marketing patterns[1], future development trend[2] and value prospect[3];most of which are qualitative description, lacking quantitative analysis. Based on micro perspective, scholars mainly start with Microblog information dissemination model, study how to obtain the maximization of information effect and marketing effect, and mainly study the optimization of information dissemination. In regard to evaluation of the influence of nodes, scholars apply different methods to measure the influence of nodes. Some focus on the sort algorithm for the influence of FollowerNum [4], some take into overall consideration the user preference, interaction between nodes and dissemination capacity [5]. With regard to evaluation of information quality, some scholars put forward a mutually enforced learning framework to predict content quality and user reputation [6],some scholars employ nDCG algorithm to evaluate and sort the Twitter information quality [7]. Thus, both overseas and domestic scholars agree that the key of Microblog marketing lies in realizing the maximization of information diffusion effect; however, quantitative study on this is insufficient, and there is a lack of comprehensive classification of influencing factors of information diffusion. The article innovatively selects the repost information cascade diffusion status formed by Microblog posting of enterprises as the key to present Microblog marketing effect, applies multiple regressions, variance analysis and other quantitative analysis means, which make up for the deficiency of the previous studies,and collects large-sample actual data for demonstration, combining the theory with the practice and being pretty convincing with Xia Chen et al J. Chem. Pharm. Res., 2014, 6(5):1529-1535 ______________________________________________________________________________ 1530 practical promotion value. II.BUILDING INFLUENCE MODEL OF KEY FACTORS ON ENTERPRISE MICROBLOG MARKETING EFFECT The article applies the diffusion effect of “repost information cascade” to measure the Microblog marketing effect, builds Microblog information dissemination model and analyzes the information cascade diffusion effect and its influence factors. Dependent variable –the measurement index of information diffusion effect: Studies at home and abroad are taken for reference, and two indexes of dissemination scale and dissemination speed [4,5,8] are used for measuring the diffusion effect of repost information cascade. Independent variable – influence factors: As for the influence factors, the study takes the classic BASS diffusion model for reference: (1) Microblog factors: Two factors are included. Additional information: consider whether image/ video, URL, @ others and #topic# are covered; PostTime: including the time factor with a day as a cycle according to the activity routines of Sina Microblog users. (2)Enterprise node characteristics Enterprise node characteristics indicate influence of enterprise nodes in the social network, including factor: node FollowerNum. (3)Repost node characteristics and their acceptance behavior. The acceptance behavior of the intermediate nodes in the diffusion path of a Microblog posting can influence the overall diffusion through stimulating the acceptance behavior of the subsequent nodes. The study defines hub nodes as nodes with many social relation chains; it ranks all the repost users of a certain Microblog posting according to their FriendNum and FollowerNum, uses the setting of critical value by existing studies, and defines two types of hub nodes: acceptance-type hub: nodes whose FriendNum ranks top 20% among all the repost users; dissemination-type hub: nodes whose FollowerNum ranks top 20% among all the repost users. The theoretical model is as follows: Figure 1:Influence factor model of repost information cascade diffusion effect III.RESEARCH HYPOTHESIS 3.1 Influence of Microblog factors on diffusion effect of repost information cascade H1a: Compared with Microblog postings in plain text, Microblog postings including image/ video have a larger RepostNum. H2a: Compared with Microblog postings in plain text, Microblog postings including image/ video are more likely to be reposted in a short time. H3a: Compared with Microblog postings in plain text, the information cascade formed by Microblog postings including image/ video are more likely to survive for a longer time. H1b:The Microblog posting with URL has larger RepostNum than that of plain text. H2b: The Microblog posting with URL is more likely to be reposted in a short time than that of plain text. H3b: The Microblog posting with URL is more likely to have a long-life information cascade than that of plain text. H1c:The Microblog posting with @ has more repost times. H2c: The Microblog posting with @ is more likely to be reposted in a short time. H3c: The Microblog posting with image or video is more likely to have a long-life information cascade. Xia Chen et al J. Chem. Pharm. Res., 2014, 6(5):1529-1535 ______________________________________________________________________________ 1531 H1d:The Microblog posting with # has a larger RepostNum. H2d: The Microblog posting with # is more likely to be reposted in a short time. H3d:The Microblog posting with # is more likely to have a long-life information cascade. H1e: The RepostNum will be increased when the Microblog is posted in an active time. H2e: The Microblog posted in an active time will be more likely to be reposted in a short time. H3e:The Microblog posted in an active time is more likely to have a long-life information cascade. 3.2 The influence of enterprise node characteristics on the diffusion of repost cascade H1f:There is a positive correlation between FollowerNumof enterprise nodes and RepostNum. H2f:The FollowerNum of enterprise nodes will influence the dissemination speed. The more the FollowerNum, the more easily the Microblog will be reposted in a short time. H3f:The FollowerNumof enterprise nodes will influence the survival probability of repost cascade. The more the FollowerNum, the longer the information cascade will exist. 3.3 The influence of the heterogeneity of repost nodes and the acceptancebehavior on the diffusion of repost cascade H1g: The reposting of Hub node occurs in the early stage of information cascade diffusion. H2g: The reposting of Hub node is favorable for accelerating the dissemination of information cascade. H3g: The reposting of Hub node is favorable for enlarging the dissemination of information cascade. H4g:Acceptance-type hub has a greater influence than diffusion-type hub on the diffusion speed of information cascade. H5g:Diffusion-type hub has greater influence than acceptance-typehub on the diffusion scale of information cascade. IVDATA ANALYSIS It analyzes the influence of Microblog factors and enterprise node characteristics on the RepostNum in the method of multiple linear regression and on the repost speed in the methods of survival analysis and linear-regression analysis; and the influence of hub nodes on RepostNum and repost speed in the methods of variance analysis and regression analysis. 4.1 The influences of Microblog factors and enterprise node characteristics on the RepostNum 4.1. 1 Model variable setting The variables of regression model are set as follows: Dependent variable: RepostNum – the repost times during the observation period. The logarithm transformation (logRepostNum) is performed to increase the fitting degree of the model. Independent variable: (1) Microblog factors:  Additional information:  Six indexes: “Include img or not (IncludeImg)”, “include URL or not (IncludeURL)”, “include @ or not (Include@)”and“include # or not (Include#)”  The representations of dummy variables are set. When it takes 1, the index will be “yes”.  Time point of posting:  PostTime: It is divided into four phases based on the activeness of posting in 24 hours: rest at night (19:00-24:00), on and off work (8:00-10:00, 17:00-19:00), working (10:00-17:00) and sleeping (0:00-8:00). The dummy variable areas are divided based on the four periods of time. (2) Characteristics of enterprise nodes:FollowerNum RESULTS AND DISCUSSION 4.1. 2 Result of data analysis The result of significance test indicates that the general Sig. (significance level) of the model is 0.00, less than 0.05. Thus the regression model is effective.Table 1 refers to the regression coefficient of the model. The two-tailed test shows that except the Sig. of PostTime is greater than 0.05,the Sig. of rest variables is less than 0.05. And it can be seen from the standardized regression