To improve the availability and validity of data, the data source of this paper consists of 3189 articles pushed by five popular public WeChat accounts at the Central University of Finance and Economics (CUFE) in 2019. These are the five most influential public accounts with the most subscriptions. These five public accounts are more representative, both official and unofficial, both graduate and undergraduate students. The five popular public WeChat platforms are “CUFE”, “What CUFE”, “CUFE Bengdou”, “CUFE Student Affairs Office” and “CUFE Graduate Student Union.”

In this paper, the most authoritative index in evaluating the influence of WeChat in China, the WeChat Communication Index (WCI), serves as the research parameter. According to the setting of the WCI algorithm, the attention to WeChat content is reported in the reading index, WCI(R); the response rate is represented in the thumbs-up index, WCI(Z); and the WCI calculated by weight reflects the “heat”. The attention and response rate of college students to the content of network education are important measures of the effectiveness of network education (Teresi, 2016). In the WCI algorithm, attention mainly refers to how often people read an article, which is used to measure the coverage of information transmission (Tyrer, 2019). The response rate mainly concerns the interaction between fans and public WeChat accounts after reading the article. The WCI heat calculated by combining the two can more comprehensively reflect the content and interest points to which college students pay attention (Lin & Jian, 2019). The specific indicators and calculation formulas are shown in Table 1.

We ranked all tweets according to their reading volume from highest to lowest and selected the top 50 tweets as the analysis sample. As shown in Figure 1, the highly read tweets come from the public accounts “CUFE”, “What CUFE” and “CUFE Bengdou”. The possible reason for this situation is that tweets themselves have a strong appeal, and a large number of readers follow these three public

accounts. From the perspective of reading volume alone, the top three tweets have been read 66,057; 57,771; and 56,063 times, respectively, far exceeding the total number of teachers and students. This finding indicates that the readers of these three public accounts have gone beyond the scope of the university and may include alumni, examinees, and the general public.

To be specific, the seven categories all take the form of pictures, charts, audio, or video combined with words, which also reflects the reading habits and preferences of readers. Tweets that simply use text are not attractive enough to retain readers. Among the types of tweets, campus culture is the most widely read of the top 50 tweets, accounting for 50%, followed by nine studies on employment (18%), eight news stories (16%), six articles in the life services category (12%), and one mainstream value category and one notification category, which account for 2% combined. As displayed in Figure 2, according to the data, students are most interested in tweets that reflect the history of the school, campus cultural life, campus events for students, and campus figures related to them. Paying attention to study and employment ranked second in terms of WeChat reading, which is consistent with the idea that students focus on these issues. The fact that the news report category ranks third reflects, to some extent, that WeChat has become an important channel for students to receive updated school information (Zhao & Wei, 2017).

The ratio of the number of tweets thumbs-ups (Z) to the number of tweets read (R) is defined as the thumbs-up rate of tweets to evaluate readers’ recognition, liking, and support for a tweet. The higher the thumbs-up rate, the higher the reader’s recognition of their views and values becomes. Using the WCI algorithm, we calculated the thumbs-up rate of all tweets in 2019. The top 50 tweets with the thumbs-up rate were selected as the analysis samples.

According to the official accounts, the top 50 tweets in terms of the thumbs-up rate include “What CUFE”, “CUFE Student Affairs Office”, “CUFE” and “CUFE Graduate Student Union.” However, “CUFE Bengdou” tweets, which rank high on the most-read list, do not appear in the thumbs-up top 50. To some extent,

this finding shows that students at CUFE have a lower recognition for articles published by “CUFE Bengdou” than other public accounts. After analyzing the sections of the public account “CUFE Bengdou”, such as postgraduate entrance examinations, real exam questions, trampoline Taobao, and rental graduation clothes, the research team found that the possible reason was that the tweets of “Zhicai Trampoline” as a public account used for commercial purposes generally had a stronger inclination toward seeking commercial profit. Most of the tweets themselves are not original and do not express explicit opinions. Readers do not have an emotional reaction or value judgments of the tweets while reading them; thus, they do not experience emotional communication or value resonance. Therefore, it is difficult for such tweets to stimulate readers to perform “thumbs-up” actions (Wang, Zhao, & Wang, 2015).

According to the proportion of the public accounts of the top 50 tweets in terms of the thumbs-up rate, there are 31 “What CUFE” tweets, accounting for 62%, followed by the “CUFE Student Affairs Office” category with eight tweets (16%), seven “CUFE Graduate Student Union” tweets (14%), and four tweets from “CUFE” (8%), as shown in Figure 3.

The tweet content types consist of five categories, including news reports, campus culture, study and employment, life services, and mainstream ideology, but not notification or voting. Among them, there are 15 news reports (30%), 12 concerning mainstream values (24%), 11 on campus culture (22%), eight on life services (16%), and four studies on employment (8%).

By analyzing the content types, we can see that students are more likely to make clear value judgments on news articles. In particular, we should pay attention to the large proportion of tweets about mainstream values, which indicates that college students are not as opposed to articles about mainstream values and education as previously thought. Through further analysis of the mainstream

value education articles, which account for up to 24%, we can find that these articles mainly involve the spirit of volunteerism, a focus on the two sessions, advanced figures, and so on. In other words, the ideological consciousness of the students at CUFE is relatively positive, which is recognized and in line with mainstream values (Lovejoy & Saxton, 2012).

Regarding the form of tweets, the tweets related to articles with a high rate of likes mainly adopt the text + picture form. Compared with the various forms of highly read articles (e.g., audio and video), the presentation form of highly liked tweets is somewhat monotonous. Thus, it can be seen that diversified forms of tweets can attract students to click and read, as well as improve the reading quantity of articles, but this approach does not necessarily result in positive feedback from students (Vickie, 2015). Furthermore, the influential factor that makes students identify with an article is the content of the article.

As shown in Table 3, all tweets were counted according to the time of publication. By analyzing the relationship diagram between the release time of tweets and the number of tweets read, it can be seen that, from the time node, tweets published at 9:00 am, 12:00 noon, and 14:00 are read the largest number of times. In terms of time distribution, the number of tweets posted during the day is higher than that at night. However, from the perspective of college students’ full-day activities, this is not a positive phenomenon because students have classes and must study during the daytime. This finding may reflect the widespread phenomenon of students using WeChat in class and study periods.