Public film review is an important reference standard for film quality evaluation. 67.9% of users in China choose to use Weibo to share their personal film-watching feelings, and more than 80% of users say that word of mouth about a film on Weibo is easy to influence their film-watching behavior. This paper collected 236,011 Weibo topic data of 41 Chinese films in 2022. Sentiment time curve clustering model is used to explore the influence of sentiment changes on consumers’ film preferences and thus on film success. By combining the competitive distance measurement method and the partitioning algorithm, this paper selects the K-shape+SBD method with the best profile coefficient performance to cluster the sentiment time series data, and then the study found that the Weibo topic text clustering of 41 Chinese films was divided into four categories, showing four trends of “M-type”, “slowly descending”, “forward-inverted V-type” and “slowly rising” respectively. The changing trend of sentiment will significantly affect the success of films. Films with “slowly rising” are more likely to achieve commercial and word-of-mouth success, “M-type” and “forward-inverted V-type” are more likely to achieve better word-of-mouth, and “forward-inverted V-type” can attract more users to post film reviews.
KEYWORDS: Analytical research, Mining, Detection and tracking algorithms, Internet, Network security, Social networks, Information science, Data analysis, Algorithm development
COVID-19 has caused a large number of online public opinion incidents. How to timely and effectively guide the resulting network public opinion has become an urgent problem to be solved. This paper collects more than 130,000 original Weibo posts during the Wuhan “city closure” incident, and analyses the topic characteristics of the incident on the basis of user classification through topic models and community detection algorithms. It was found that during this period, the government responded quickly to the epidemic and gained public support. For different Weibo users, officially certified users mainly publish information about the epidemic and epidemic prevention measures. Personally certified users mainly forwarded and transmitted official information actively, and they also expressed their opinions and made suggestions. Non-certified users actively expressed their emotions and opinions, so they were important users that reflect public opinion.
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