| With the development of the internet,online communities and user-generated content(UGC)produced by users can offer more and more significantly high value that cannot be ignored for marketing practicer.On the one hand,firm can make money by placing advertisements in online communities,and they can also use online communities for marketing activities.On the other hand,the UGCs produced by users in online communities reflects the users’ own thoughts,opinions,attitudes,etc...So,extracting information from UGCs can provide marketing insights for marketing practicer.Therefore,both online communities and UGCs have attracted the attention of scholars.Since UGCs are unstructured data,previous studies have used text analysis to analyze UGCs.Through a summary analysis of related literature studies,this dissertation found that if marketing practicer try to understand and quantify information hidden in UGCs,then marketing practicer need to pay attention to the following three the indicators which are the emotion of UGCs,the language/linguistic style matching(LSM)of UGCs,and the topics of UGCs.Previous studies have shown that firm can use these three indicators extracting from UGCs to improve marketing practices,such as using UGCs’ emotion to predict sales,using UGCs’ LSM to understand the probability of users’ continued participation in online communities,and UGCs’ topics to understand or monitor users’ attitudes or perception towards brand.Although the existing research has carried out quite a lot of research focused on these three indicators of UGCs,and confirmed that UGCs is something that firm needs to pay attention to.However,the existing literature has failed to solve the following problems: Given that UGCs in online communities is a valuable thing for firm,what can firm do to influence UGCs?In order to answer the question mentioned above,this dissertation focused on firm feedbacks and the above-mentioned three indicators of UGCs,using data from the MIIUI forum,instructed by the emotional contagion theory,the communication accommodation theory,and the variety-seeking theory,then started three researched,namely: What’s the effect of firm feedbacks on UGCs’ emotion? What’s the effect of firm feedbacks on UGCs’ language style matching? What’s the effect of firm feedbacks on the variety of UGCs? What needs to be explained is that the variety of UGCs is measured by the number of topics that users choose to use in the production of UGCs.The research of this article finally got many conclusions that were summarized as follows.Firstly,based on the emotional contagion theory,this dissertation used a vector auto regression(VAR)model to analyze the mutual influence of three different emotions from different sources: emotion of firm feedbacks,emotion of UGCs,and emotion of other users’ feedbacks,in the online community at the overall level.The results showed that the emotion of the firm feedbacks affected the emotion of UGCs and other users,that is,the emotion of the firm feedbacks will be transmitted to the feedbacks of UGCs and other users.However,emotion of firm feedbacks has different effects on emotion of UGCs and emotion of other users’ feedbacks in the two dimensions of mean and volatility.For example,an increase in the mean of emotion from firm feedbacks will lead to the mean of emotion from UGCs to increase first and then decrease,but it will only make the mean of emotion from other users’ feedbacks decrease.In addition,the duration of the mutual influence of emotions from different sources was relatively short,and the most important contributor to the changes in emotions from different sources was itself,but the mean of emotion from firm feedbacks was the secondary contributor to the mean of emotion from the other two sources.Secondly,based on the communication accommodation theory,this dissertation used the panel fixed effects model to study the effect of firm feedbacks on the LSM of UGCs,and to explore the boundary conditions of such effect.The results showed that the total number of firm feedbacks and the total text length will affect the LSM between UGCs and firm feedbacks,but the signs of these two effects are opposite.The more the total number of firm feedbacks was,the higher the LSM between UGCs and firm feedbacks would be.However,the longer the total length of the text of firm feedbacks was,the lower the LSM between UGCs and firm feedbacks will be.In addition,the user’s own characteristics will moderate the effect of firm feedbacks on UGCs’ LSM.The more positive the emotion of the user’s published content was,the smaller the negative effect of the total text length of the firm feedbacks on UGCs’ LSM.At the same time,the longer the total text length of the user’s published content was,the smaller the positive effect of the total number of firm feedbacks on UGCs’ LSM was,but the negative effect of the total length of the text of the firm feedbacks on the LSM of UGCs will be offset.Finally,these effects of firm feedbacks on the role of UGCs’ LSM,including the moderator effect of users’ own characteristics,has only been confirmed in active user groups,but has not been confirmed in inactive user groups.Finally,based on variety-seeking theory,this dissertation used the topic modelling to extract the topics of UGCs,and then measured the variety of UGCs’ content based on whether the user chooses a single topic or multiple topics when producing UGC.Using logistics regression,negative binomial regression model and other models.This paper studies the user’s own tendency to seek the variety in UGCs’ production.At the same time,this paper also explores the effect of firm feedbacks on users’ tendency to seek the variety in UGCs production.The results showed that users will show a preference for the variety in UGCs’ production,that is,if user has produced more single-topic UGCs,the user’s tendency to produce multi-topic UGCs in the next production will increase,and the tendency to produce single-topic UGCs will decrease.Similarly,if user has produced more multi-topic UGCs,the user’s tendency to produce single-topic UGCs in the next will increase,and the tendency to produce multi-topic UGCs will decrease.Moreover,the higher the LSM between firm feedbacks and UGCs,the tendency of users to produce single-topic and multi-topic in the future will increase,which was not contradictory as it was proved to be that the LSM between firm feedbacks and UGCs will make users produce more UGCs.The research in this dissertation has many practical implications for the UGCs management.First,firm can influence UGCs emotion through feedbacks.However,firm need to carefully consider how to adjust the mean and volatility of emotion in feedbacks.This is because that the effect of emotion from firm feedbacks on emotion from UGC is reflected in the mean and volatility of emotion.Moreover,since the effect of emotion from firm feedbacks on emotion from UGCs is transient and the contribution is small,firm need to proactively participate in online communities and provide feedbacks frequently.In addition,if a firm wants to predict the changes in emotion in online communities,they need to consider the mean and volatility of emotion as well as the sources of emotion.This is because emotion from different sources have mutual influence on the mean and volatility of emotion.Thus,firm needs to consider from an overall view.Second,firm can influence UGCs’ LSM through feedbacks.However,firm need to carefully choose the total number of firm feedbacks and the total text length of firm feedbacks.This is because an increase in the total number of firm feedbacks will increase the LSM between UGCs and firm feedbacks,but an increase in the total text length of firm feedbacks will reduce this LSM.Moreover,the user’s own characteristics such as the emotion of the user’s published content,and the total text length of the user’s published content will moderate the effect of firm feedbacks on UGCs’ LSM.Therefore,firm needs to pay attention to the characteristics of users when giving feedbacks and increase the LSM of UGCs.In addition,the effect of firm feedbacks on UGCs’ LSM has been confirmed in relatively active user groups,but it has not been confirmed in relatively inactive user groups.Therefore,if a firm try to influence LSM between UGCs and firm feedbacks,the firm should choose a relatively active user group.Finally,firm can influence the variety in UGCs through firm feedbacks.Users themselves will show an intrinsic tendency to seek variety in UGCs production,and the higher the LSM between firm feedbacks and UGCs,users themselves will show a higher and lower tendency to seek variety in UGCs production.But this is not a contradiction,because users will produce more UGC,then users can show a higher tendency to seek variety in UGCs.In general,to increase the number of UGC or to promote more variety of UGC,firm should increase the LSM between firm feedbacks and UGCs.The research in this article also has some contribution in theory which were shown as follows.First,previous studies have paid attention to the role of the mean of emotion in emotional contagion,but have neglected that the same mean of emotion may have different volatility at the overall level,while the research of this article considers both the mean and volatility of emotion in emotional contagion,and confirms that the mean and volatility of one source’s emotions may affect the mean and volatility of another source’s emotions.In addition,previous studies have failed to answer what role firm feedbacks played in emotional contagion.The research in this dissertation filled this gap.Second,previous studies have shown that UGCs’ LSM can reveal or predict user behavior,but they have not paid attention to how firm can influence UGCs’ LSM.This dissertation studies the total number of firm feedbacks and the total text length of firm feedbacks will affect the LSM between UGC and firm feedbacks.Specifically,the more the total number of firm feedbacks were,the higher the LSM between UGCs and firm feedbacks will be.However,the longer the total text length of firm feedbacks was,the lower the LSM between firm feedbacks and UGCs will be.And the research in this article further shows that the user’s own characteristics-the emotion of the user’s published content and the total length of the article of the user’s published content will moderate the effect of firm feedbacks on the LSM of UGCs.In addition,the research in this article also explored the heterogeneity of user groups.The results showed that the effect of firm feedbacks on UGCs’ LSM existed in relatively active user groups,but had not been confirmed in relatively inactive user groups.Finally,previous studies have found that users will show variety-seeking behavior in purchasing goods,but previous studies have failed to answer whether users will show variety-seeking tendencies in the production of UGCs,and whether firm can influence this tendency.This article used the results of the topic model to measure the variety of UGCs’ content,and found that users will show a tendency to seek variety in the production of UGCs,and the LSM between firm feedbacks and UGCs will promote the variety-seeking tendency in UGCs production at the same time.The higher the LSM between the firm feedbacks and UGCs was,the more UGCs users will produce,and the users will show a higher tendency to seek variety in UGCs production. |
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