CROSS-CULTURAL EXAMINATION OF SAMSUNG’S MARKETING STRATEGIES ON DOUYIN AND TIKTOK

This thesis project aims to investigate the use and effects of tech companies’ content marketing strategies on Douyin and TikTok through a cross-cultural case study on Samsung. Qualitative content analysis is used to analyze Samsung’s 60 high-performing and lowperforming Douyin and TikTok posts to examine the use of content gratification factors and the executions of the hashtag, influencer and metanarrative strategies. Quantitative sentiment analysis is used on 1,400 comments to evaluate public feedback through engagement and sentiment scores. Based on a modified internet gratification framework, results revealed a consistent focus on information-seeking, personal status and aesthetic experience gratifications among marketers and audiences across cultures with failed content motivations of monetary compensation and diversion. Qualitative content examinations also indicated a potentially culture-based strategy use and effects on Douyin and TikTok. As metanarrative outweighs other strategies with culturally consistent central and supportive narrative patterns, hashtag and influencer strategies attained moderately supportive engagement and sentiment with successful challenge-focused hashtags on TikTok and effective influencer and brand partnership tactics on Douyin. While experience sharing and group recognition remain part of the primary focuses in user comments, user-driven organic sharing was also a significant comment function for Douyin users. While future research is required for more generalizable results among tech brands, all the preliminary results and analyses shed light on the existing marketing patterns and user interactions for the current tech marketing strategies on TikTok and Douyin while offering exploratory culture-based perspectives for cross-cultural TikTok marketing campaigns.Master of Art

明初文化格局中的地方儒家與臺閣文風

明初文學中一個引人注目的現象是永樂至宣德間臺閣文風的盛行。以朝廷爲主導的臺閣文風，如何成功地覆蓋了在野的、地方的、下層的廣泛社會文化場域？追溯其來龍去脈，地方儒學官是值得關注的群體。相較於明中後期學校的荒廢，明初是地方儒學發展的興盛期。地方儒學官在政治、文化生活中作用顯著，永宣時代的臺閣要員就多有任教地方的仕宦經歷；經由考竅選拔、親族鄉誼等聯結因素，地方儒學官與臺閣要員往來密切，交流頻繁，大量酬赠詩序體現出受臺閣影響的旨趣和文風。臺閣體的長期風行，是廣泛的士人群體參與的結果，體現了不同社會階層之間的文化整合。臺閣文風可視爲明初打破朝與野、地方與中央二元對立從而實現以皇權爲中心的政治大一统格局的文化操誌

DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation

Sequential recommendations have made great strides in accurately predicting the future behavior of users. However, seeking accuracy alone may bring side effects such as unfair and overspecialized recommendation results. In this work, we focus on the calibrated recommendations for sequential recommendation, which is connected to both fairness and diversity. On the one hand, it aims to provide fairer recommendations whose preference distributions are consistent with users' historical behaviors. On the other hand, it can improve the diversity of recommendations to a certain degree. But existing methods for calibration have mainly relied on the post-processing on the candidate lists, which require more computation time in generating recommendations. In addition, they fail to establish the relationship between accuracy and calibration, leading to the limitation of accuracy. To handle these problems, we propose an end-to-end framework to provide both accurate and calibrated recommendations for sequential recommendation. We design an objective function to calibrate the interests between recommendation lists and historical behaviors. We also provide distribution modification approaches to improve the diversity and mitigate the effect of imbalanced interests. In addition, we design a decoupled-aggregated model to improve the recommendation. The framework assigns two objectives to two individual sequence encoders, and aggregates the outputs by extracting useful information. Experiments on benchmark datasets validate the effectiveness of our proposed model

Empirical prediction of blast-induced vibration on adjacent tunnels

The blast-induced vibration during excavation by the drilling and blasting method has an important impact on the surrounding buildings/structures and auxiliary equipment. In particular, with the development of tunnel engineering, the impact of blasting vibration on tunnel construction has attracted extensive attention. Based on literature data statistics, this paper first explored the performance of several commonly used empirical equations in predicting the propagation and attenuation characteristics of blasting vibration on adjacent tunnels. Secondly, the relationships between the empirical parameters of the blasting vibration prediction equation and the geological strength index (GSI) of tunnel surrounding rock were discussed, and two new blasting vibration prediction equations based on site rock GSI were established to approximately predict blast-induced vibration on adjacent tunnels. Finally, the application feasibility of the established prediction equation in practical engineering was discussed based on field test data. The research results show that under the condition of multiple groups of data, the prediction performance of various prediction models does not differ significantly. With the increase of the GSI of the surrounding rock mass of the adjacent tunnel, the site coefficients β and k of the blasting vibration prediction equation in predicting PPV (peak particle velocity, resultant velocity) both show a decreasing trend as a whole. The site coefficient k is generally within 3,000. Two new empirical prediction equations of blasting vibration propagation and attenuation on adjacent tunnels under different site conditions were established: Eq. (14) for PPV and Eq. (15) for PPVi (max) (maximum value of the three component velocities; i = x, y, z represent peak component particle velocity). The verification analysis of five sites shows that these two equations have a certain practical application value. Compared with other empirical equations, these two equations do not need regression fitting blasting vibration data, they only used the GSI of the site rock mass, and they are more easy to use in the field when there is a lack of monitoring data