A Study on the Information Diffusion Behavior of Social Media Users-the Case of Mobile 01
| Autor: | CHEN, JIAN-ZHONG, 陳建忠 |
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| Rok vydání: | 2017 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 This paper is focus on how to identify the roles of information diffusion behavior, and realize the forming mode of the influencers of different mobile brands. For this purpose, we will establish 6 social network models from the forum of Mobile01 which is one of the most famous EWOM platforms in Taiwan. And then through the quantities of response to filter the influencers of power low. Finally, we use social network analysis to realize the influencers’ information diffusion participate behavior and also use Binary Logistic Regression to identify the influencers and non-influencers of topological feature. This result will expose that how to become an influencer is not only decided by quantities of response but also by reviews popularity. Following the feature of different brand, influencers have dissimilar network position. This paper’s major contribution is providing an objective and quantified method to identify the information diffusion of different role. And then from this analysis, we can realize features of information diffusion, roles position, and the forming mode of the influencers about different brands. Finally we find the forming mode of the influencers can be classified by three methods: response orientation, popularity orientation and complex orientation. Through this analysis, we can use the different forming mode to accurately screen out the influencers. And we find the different mobile brands have dissimilar information diffusion environment which could be divided into individual, group and overall. Then we can use this three categories to make message management easier. In order to obtain real and first-hand data which also different from other papers, rather than questionnaires or opinion polls, we use the Web crawler to grab users’ historical comments which left on the sites. So it will be more valuable for future research. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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