Academic Journal of Humanities & Social Sciences, 2025, 8(2); doi: 10.25236/AJHSS.2025.080219.
Xin Liu1, Xinyao Qiu1, Jin Li2
1School of International Culture and Communication, Jingdezhen Ceramic University, Jingdezhen, China
2School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, China
This paper focuses on the communication channels of Chinese ceramic culture international communication and two categories of sentiment analysis approaches. In the current digital age, social media, online forums and e-commerce platforms have emerged as crucial channels for promoting Chinese ceramic culture. Previous studies, such as those by scholars like Sahar A. El Rahman, have explored sentiment analysis on social media. As for sentiment analysis approaches, the lexicon-based approach, relying on pre-constructed sentiment dictionaries, and the machine learning-based approach, which learns from a large amount of labeled data, are both valuable. The practical application of these approaches in different communication channels is analyzed. For Chinese ceramic culture international communication, sentiment analysis approaches can judge the sentiment orientation of audience reviews on social media, online forums and e-commerce platforms. Through analyzing online audience reviews, we can not only understand the international audiences’ attitude towards Chinese ceramic culture, but also enables us to take targeted measures to enhance its global influence and cultural communication power.
Ceramic Culture, Communication Channel, Audience Review
Xin Liu, Xinyao Qiu, Jin Li. Research on Communication Channels and Audience Reviews of Chinese Ceramic Culture International Communication. Academic Journal of Humanities & Social Sciences (2025), Vol. 8, Issue 2: 131-135. https://doi.org/10.25236/AJHSS.2025.080219.
[1] S. A. El Rahman, F. A. AlOtaibi and W. A. AlShehri. (2019) Sentiment Analysis of Twitter Data. 2019 International Conference on Computer and Information Sciences (ICCIS).
[2] V. Ramanathan and T. Meyyappan. (2019) Twitter Text Mining for Sentiment Analysis on People’s Feedback about Oman Tourism. 2019 4th MEC International Conference on Big Data and Smart City (ICBDSC).
[3] M. M. Wen, D. Y. Yang and C. P. Rosé. (2014) Sentiment Analysis in MOOC Discussion Forums: What does it tell us. Educational Data Mining.
[4] J. Carrillo-de-Albornoz, J. Rodríguez Vidal, L. Plaza. (2018) Feature engineering for sentiment analysis in e-health forums. PloS ONE, Volume 13, Issue 11: e0207996.
[5] Y. Basani, et al. (2019) Application of Sentiment Analysis on Product Review E-Commerce. Journal of Physics: Conference Series. 1st International Conference on Advance and Scientific Innovation (ICASI), Volume 1175: 012103.
[6] S. A. S. Neshan and R. Akbari. (2020). A Combination of Machine Learning and Lexicon Based Techniques for Sentiment Analysis. 2020 6th International Conference on Web Research (ICWR).