3 angles to explore the rules of Zhihu hot list

Hot searches/hot lists have always been one of the places where the most traffic is concentrated.

The hot lists of each platform are, on the one hand, a barometer of current traffic; on the other hand, they are a battleground for traffic manipulators in various fields.

So what are the rules behind these hot lists?

Today, I will take Zhihu as an example to analyze the hidden information in Zhihu’s hot list .

1. Introduction

What does the popularity of Zhihu’s hot list represent?

First, let’s take a look at what the Zhihu hot list represents?

The hot lists pushed by Zhihu are unified across the entire network, and there is no "one size fits all" approach, which means that every question on the hot list has a large exposure.

Zhihu’s hot list is updated every 2-3 hours, which means that every question has a chance to be on the hot list.

Does this mean that as long as you plan the answers to these hot questions in advance, you can get a lot of passive traffic!

So which questions can make it to the hot list?

As we all know, the hot list is ranked comprehensively through a popularity calculation formula, where popularity is a combination of page views, interaction volume, professional weighting, creation time, and time on the list.

But in the final analysis, I still don’t know how to judge whether a question can be on the hot list!

It just so happens that we geeks have such a set of historical hot list data from Zhihu. If we dig out the patterns from it, maybe we can come up with our own judgment criteria.

Based on this, I made a brief analysis from three perspectives.

2. How many questions will be on the hot list again after being on the hot list?

Geek has stored a total of 75,336 hot list data, of which at least 10,337 questions have been on the hot list again after being on the hot list!

The proportion is 13%. Although it is not a large proportion, you should know that based on the huge base, these questions that are repeatedly on the hot list are also very valuable!

Because since they can make it to the hot list for the second time, they can make it to the hot list for the third time!

These questions are natural traffic engines.

On the other hand, in terms of increasing the weight of an account, the simpler the tags used to answer the questions, the higher the weight of that field. If these tags can hit the hot list, wouldn’t that be even more powerful!

Through backend statistics, among these 10,337 repeated hot questions, the tag with the most is "life", as many as 3,500!

So even if you are selling milk powder, if you keep laying out issues with the “life” label, the probability of being on the hot list is very high!

Based on this, the tags that have been on the hot list more than 200 times are counted as follows. Each tag contains a large amount of Zhihu exposure.

If you want to make a layout on Zhihu, it is a very good choice to make a layout based on these repeated tags + questions that can be on the hot list.

3. Who raised the hot questions?

Zhihu not only has a group of users who love to answer questions, but also a group of users who love to ask questions. Today I discovered that this user has mentioned thousands of users in total.

Then let’s think about it the other way around: who raised these hot questions? If some users can ask many hot questions, should we focus on these users' questions?

According to backend statistics, most of the hot questions were raised by anonymous users, with 12,594 questions, as shown in the figure below (the horizontal axis is the number of hot questions raised, and the vertical axis is the author of the question).

But excluding anonymous users, Zhihu users and those who have logged out, we can clearly filter out these KOLs who ask questions.

From the picture we can see that the person who asked the most hot questions is Mitsujiro Sasaki, who asked 586 hot questions. He can be called the little prince of questions. Some people even started a thread specifically asking whether he is an internal employee of Zhihu.

If you further classify these KOLs who ask questions, and focus on the KOLs who ask questions in your category, and actively answer the questions whenever they ask questions, the probability of grabbing the hot list will be greatly increased!

4. What is the question that has appeared on the hot list the most times?

We know that some questions will be on the hot list again, so what are the questions that have been on the hot list the most times?

According to backend statistics, the maximum number of times it has been on Zhihu's hot list is 15. The question is "What are some methods for finding words that you regret not meeting earlier?"

So what is the time pattern of it appearing on the hot searches multiple times?

I calculated the time difference between these 15 appearances on the hot list, made a summary, and then generated the following sketch. The horizontal axis is the sequence of appearances, and the vertical axis is the time difference between two appearances:

From the figure, we can see that the time difference of up to 8 times is almost the same, which means there is a high probability that it will be on the hot list for the 16th time after such a fixed time.

Does this give you a feeling like the "menstrual posts" in the forums of the past? This is obviously a cyclical problem, which shows that such topic material is also a pain point for the public at fixed times.

If we study it further, we will find that this question is on the hot list before the exam, thus discovering the internal social reasons why it is on the hot list.

There are also many of these periodic hot topics, such as what are the goals for 2021, the summary of 2020, and what gifts to give on Valentine's Day, which can also be planned in advance.

V. Others

Of course, in addition to the answers to the three major questions above, we can also use data statistics to discover the data limits of Zhihu’s hot questions!

For example, what is the minimum popularity required to be on the hot list?

Answer: The minimum required is only 60,000. There are many such questions.

How many answers are needed to be on the hot list?

Answer: You only need at least 8 answers to be on the hot list.

How many followers are needed to make it to the hot list?

Answer: You only need at least 23 followers to be on the hot list.

What is the minimum number of views required to be on the hot list ?

Answer: You only need at least 1,841 page views to be on the hot list.

If I didn’t say the above three questions were hot list issues, when you saw such data, you probably wouldn’t believe that it was extracted from the hot list!

What does this mean? This shows that the threshold for Zhihu’s hot list questions does not need to be very high, you just need to explore its key factors.

So what is the key factor?

Let’s look at the 30-day data for a hot question this afternoon. What can you see?

First look at the browsing increment of the question:

Let’s look at the incremental number of answers to the question:

Finally, let’s look at the increment of likes for the question:

It was on the hot list at 11:23, but its answers and likes did not increase much compared to the past, but its reading volume had a very high growth, which means that it might be after some high-powered people answered the question and took relevant actions, and promoted it to get good positive and negative feedback, and then obtained hundreds of times higher reading increments than usual in a short period of time, and then was sent to the hot list.

This shows that as long as the reading increment of a question is monitored, there is a high probability that it will be on the hot list. Conversely, if you want to push the question to the hot list, referring to the above method is one of the options.

Like the question below, it was pushed to the hot list, but lost a large number of likes in a short period of time, which means that there is a high probability that it was pushed there by "brushing likes".

VI. Conclusion

OK, let's summarize. We have done some digging through the historical Zhihu hot list data and have come to some relatively superficial conclusions:

• Questions that repeatedly appear on the hot list can be planned in advance to obtain a large amount of passive traffic.
• Tags for questions that are repeatedly on the hot list can be arranged in advance to increase the weight of large traffic.
• Some KOLs who ask questions can be monitored in advance, after all, the questions that make the hot list are raised by them.
• The problem of being on the hot list is that it is pushed up by the increase in reading per unit time. Conversely, there is also a probability that the Zhihu hot list can be created in this way.

Author: Yihang

Source: Page Talks Growth