| The implementation of artificial intelligence has become mainstream in the development of social media due to its advantages of automatic data processing, content generating and efficient interaction with customers. This thesis utilized a mixed research method, including an internet-based questionnaire survey and a semi-structured interview, to identify how artificial intelligence could help improve customers' experiences when using the Chinese website AutoHome as a tool to search vehicle resources and information. A review of the literature indicates three main factors; relevance, updating frequency and degree of accuracy, that could significantly influence the effectiveness of applying AI in the social media industry. On this theoretical basis, the thesis determines three explanatory variables and collects primary data from respondents through a survey. An OLS multivariate linear regression model with critical evaluation is used to identify how customers' visiting frequency is influenced. The statistical results demonstrate that updating frequency and peoples' dissatisfaction on content relevance will cast a substantial impact on their visiting frequency, while people rarely care about what they read and comment on the information. The further interviews with three different groups of users imply that a focus on different influential factors would vary according to users' goals in using the social media platform. Based on discussions and analyses, this thesis recommends that AutoHome should build an information database to trace visitors and manage the comment area. |
