Influencing factors of pv

After a news release, you can track its PV data, usually every 5 minutes. Different channels of different brand websites have a general evaluation scale for the PV performance of the news they publish. After the news is released, the general PV value always has a rising process. We can calculate the variation range of PV per unit time from the performance of PV in different periods. Experienced network editors can roughly predict the PV peak level of this news after several five-minute data accumulation. If this level is not satisfactory, the editor should take some measures, such as "optimizing" the title or adding other eye-catching elements, such as pictures. Generally speaking, through such "processing", the pv performance of a news can be improved and reach a new peak.

In other words, the editing method of online news affects the pv value.

What other factors affect PV? At least these factors:

Press release time

In different time periods, the number of people surfing the Internet is different, and the number of people visiting the website is also different. So sometimes the fluctuation of PV value is mainly due to the natural fluctuation of the number of people surfing the Internet in different time periods. The same news, released in different time periods, PV performance will be different.

People who surf the Internet at different times have different demographic characteristics (gender, age, education level, reading purport, etc.). ), so there are 654.38 million+people online, and even a website has 654.38 million+people. The distribution of these 65,438+10,000 visits on different channels/contents is different at different times. So sometimes, the change of pv is related to the change caused by this factor. Finally, of course, there are some accidental factors (in fact, the hitchhiking factor also belongs to this). What is included? Such as weather factors, such as during SARS, and so on. What else is there? Think about it)

From this point of view, a simple pv data is actually the result of the comprehensive contribution of many factors, so sometimes the fluctuation of pv can not be completely guided and influenced by editing means. It's important to know that. Because this tells us that it is unreasonable to blindly measure success or failure with pv without specific analysis.

In social science research, this distinction between the contributions of different factors to a phenomenon is the so-called detailed analysis model. Many things that we seem to be unchanged have actually undergone great changes in their internal composition. And some seemingly changing things, their relative relationship has not changed, but simply the fluctuation of quantity.

According to the website, the daily average IP/ PV traffic is about 600/2,400, which means that today's homepage visits are 2,400 and IP visits are 600. In other words, these 600 IPS visited the home page 2400 times.

Flow is the amount of fluid passing through a certain cross-sectional area per unit time. This quantity is expressed by the volume of fluid, which is called instantaneous volume flow (qv) for short. What is expressed by flow quality is called instantaneous mass flow (qm), or mass flow for short.

Measuring the flow of fluid flowing in a certain channel is collectively called flow metering. There are various fluids used for flow measurement, such as gas, liquid and mixed fluid. The temperature, pressure and flow rate of fluid are very different, and the required measurement accuracy is also different. Therefore, the task of flow measurement is to study various corresponding measurement methods according to the measurement purpose, the type of measured fluid, the flow state, the measurement location and other measurement conditions to ensure the correct transmission of flow values.

Generally speaking, website traffic refers to the number of visits to a website, which is used to describe the number of users visiting a website and the number of pages visited by users. Commonly used statistical indicators include the number of independent users of the website, the total number of users (including repeat customers), the number of pages visited, the number of pages visited by each user, and the average stay time of users on the website.