Sina Weibo data: How do fans come here?

Every day hard code microblogging, laughing, gag, recruit cat fight dog, but in addition to zombie powder, the living fans always disappear. What the hell? Don't worry, this article tells you, fans don't come here.

There are already too many suggestions on how to increase the number of Twitter followers and how to get more tweets from Twitter. We do not know whether these proposals are effective because they are mostly based on personal perceptions and lack of real convincing evidence. In fact, Weibo is a very suitable for data analysis, so want to talk about microblogging experience, you have to use data to speak.

Microblogging data for a common user

Starting August 24, 2012, I looked like a narcissist, every day to see how many fans had gone up-not only to see, but also to record the number. It's been 86 days since I stuck to writing this article. The value of this data is not that it is artificially measured, but that it is unique: either Sina Weibo or Twitter does not record, or at least does not provide "attention" to the timing of the event. None of the existing microblogging-related data studies have accurate records of fan numbers changing over time. If we could get more data like this, we would be able to write one of the two equally important papers that I would like to introduce later in this article.

Here's a picture of how my fans have grown over the next 86 days. The figure above is the total number of fans, the following figure is the number of fans per day increase.

I used to think that an increase in the number of fans should be exponential: the more people who focus on you, the more influence you have, the more people will be watching you. Such differential equations are df/dt = CF, so f = e Ct. The actual growth, however, is roughly linear, df/dt= constant! In addition to a few bursts, I've probably added 10 fans a day. The figure marks 4 sudden growth events, of which the two times are larger September 15 and October 22. Not an emergency, my growth rate is fairly stable: in the two approximate lines, the first paragraph increases the average number of fans by 9.2 each day, the second section averages 10.5 a day, which also includes (2) and (3) two small jumps. If there is an exponential growth, it can be difficult to perform in such a short period of time, either in the early days of the opening of the account or when the account is already fairly well known, or itself a large scale.

So if you think the best way to increase your fans is to have a lot of good tweets, you might be disappointed. The truth is that only outbreaks can make your fans count to the last step. In the four burst events marked in the diagram:

(1) I published a close relative in the Nutshell network as far as the next: the most critical connections are not familiar friends. My September 15 microblog was forwarded more than 1000 times, and more importantly, the @ Shell network (fan 600,000) was introduced to this article in Weibo, with the result that more than 300 fans were grown within a day.

(2) This small fluctuation occurred on September 23, and I did not send a single tweet from September 16 to 24th. I don't know what the reason is, it's probably a fallout from (1).

(3) I made a blog about the epidemiological study of reincarnation. This article has little influence from the growth of the fans. Since then in the "Shanghai Book review" published "Who History of 40,000 years," still has not brought many fans.

(4) is the @cnsns (more than 30,000 fans) in micro-blog recommended to me, and this recommendation by the @ Jingwei Zhang (fan 3.42 million) forwarding, resulting in the number of fans in 33 minutes increased 321, two days increased by more than 800.

I made about hundreds of microblogs in three months. Twitter has a certain impact on increasing the number of fans that day, but in most cases it will not cause any outbreaks. This shows that the best way to increase the number of micro-Bo fans is not a micro-blog, hair bo is less than a few micro-blog to write a serious article. Of course, the most effective way is not to write articles, but by the Big V recommended. What is not recorded here is that there was an outbreak in the early days of my microblog account, which was recommended by scientific authors such as the Media man, the fan 140,000 and the Squirrel Science Club.

Big Data from celebrities

Not many people will record their fans as much as I do every day, which makes it very difficult to study the growth of Weibo accounts on a large scale. But researchers at Carnegie Mellon University and Microsoft still think of a way out. Twitter, like Sina Weibo, does not record the timing of each "attention action", but it arranges all your fans in the order of focus. Twitter also provides the first registration time for each account. So for any one of the fans, the researcher finds his registration time and finds the registration time of all the fans who have been paying attention to you before, and then puts all of the last of those times as the time of his attention. It can be imagined that this is a very imprecise estimate, but as long as the amount of data is large enough, it is still acceptable.

The article found that "recommended" is still the most important way to grow fans, even for celebrities with significant levels. The following picture shows the time curve of the Twitter account of the technology blog Anil Dash, entertainment actress Kim Kardashian and the New York Times. The growth of their fans is full of mutations, and the biggest mutations are the ones that Twitter has systematically recommended.

The event (1) is the introduction of a system referral list by Twitter, and the New York Times on this list. As soon as we see the list, the New York Times increases the number of fans a day. By April 2009, Kardashian was also added to the list, and her number of fans began to soar. Before entering the referral list, the dash's number of fans increased by 50 a day, and by the time he was added to the referral list in October, his number of fans increased by 2,500 a day! An interesting phenomenon is that the New York Times and Kardashian have slowed down since the dash came in, and the researchers are not sure what's According to the following changes, it is likely that for the New York Times, Twitter expanded its list of referrals in October, making its importance diluted. For Kardashian, it may be that she was removed from the referral list.

The event (2) is the way Twitter has changed its recommendation, classifying the recommended accounts so that users choose their own interests. The change has been a blow to the Dash and the New York Times, which has significantly reduced the number of fans per day. But Kardashian because she has not been on the referral list, her growth has not been affected, still gradually increase, or even a bit of the meaning of exponential growth.

The event (3) is another way for Twitter to change its referral style and become a customized recommendation based on the interest of each user. The New York Times and Kardashian both benefited, and the Dash was less affected, still adding around 200 fans a day.

From this picture alone, the role of system recommendation is too great. The technology blog Dash and the New York Times fan layer are almost entirely determined by the system, and only a female star like Kardashian can run out of a strong growth despite the big market-and it is said that the price of asking her to send an ad microblog is 10,000 dollars. What is the growth of these stars? Look at this picture below:

A big guy like Oprah Winfrey is on Twitter (event 1), and there's a lot of fans right away, but after the initial orgasm, the rate of powder increases more and more slowly, turning into the same trend as Ashton Kutcher. Really able to add powder faster and faster, like the exponential growth is the same as Lady Gaga and Justin Bieber idol Pie! How did their fans get here? Is it because they made high quality microblogs? Of course not.

The growth of the two fans is a reflection of their growing business in real life. Justin Bieber was a nobody in early 2009, and Lady Gaga was 2010 years old. We see some of the key events of Lady Gaga, (2) She got MTV Music Awards, (3) She was in the Emmy Award, (4) is her new MV "telephone". Events in the picture (5) It is interesting that the star Soulja Boy suddenly deleted his original Twitter account and built a new one, the fans are busy focusing on his new account, and a lot of attention to the action, so that our pictures of the stars of the relative popularity have been robbed of the limelight.

This seems obvious, even for celebrities, is the most powerful system recommendation, followed by what you do in the real world. The changes in celebrity Weibo fans are likely to have little to do with their microblog. Sina Weibo Yao Chen's fans are the most (now is already the Xie Na), but Chen Yao is not necessarily China's hottest actress, according to which can be speculated that Sina's recommendation helped.

For us ordinary people, there is no chance to be the system, and no chance to stir up the real world, want to raise fans may only rely on a few interesting microblogging. We expect these tweets to be widely forwarded because it's the only way to be seen by more people and attract new fans. But how do you get more forwarding? More importantly, is forwarding really useful?

What kind of Weibo forwarding volume is amazing

Several researchers at Palo Alto Research Center specialize in Twitter forwarding. The average number of times a tweet is forwarded should be related to two factors: the content of the microblog itself, and the number of fans who posted it. The number of fans is easy to measure, but the content of microblogs is difficult to measure, and the study can only be used in the simplest way.

One way to do this is to see if the tweets contain URL links (URLs). Tweets containing URLs are at least Yanzhiyouwu, and are more readable than the state where the clockwork is eaten. The study, which counted 74 million micro blogs (Twitter called tweets), found that all 21.1% contained URLs and 28.4% of those that were purely forwarded were URLs. The result does not seem obvious, but the two figures cited in another study in this article are 18.96% and 56.69%, respectively. In any case, introducing a message that you see elsewhere can actually increase the forwarding chance of Twitter.

Another way to get more forwarding is to take part in the topic, as well as the two "#" We often see, so that anyone who clicks on it can find all the tweets that have been written. Statistics show that 10.1% of all tweets contain topics, while those that tweet contain 20.8% of topics.

Both of these figures are prosaic and perfectly in line with our expectations. What we really want to do is the kind of microblogging that is quickly and widely disseminated, or even layered, to trigger explosive growth. But as I have previously introduced in the "common sense" understanding of the complex world, triggering such a "Twitter waterfall" is a great contingency, and even a large fan may not always be able to do so.

The study did not make it clear, but one of the more crucial facts I have observed is that occasionally sending a few tweets that are widely forwarded does not give you a significant increase in your fans. @Yaoyao521 a microblog about taxi drivers not taking the blind fare this year, which tells a good positive energy story that has been forwarded more than 13,000 times and even reported by the media. The author has sent over 5,000 tweets so far, but her fans are still only 3,608. Examples like this are not uncommon, and in many cases they are not-and I haven't been paying attention to them for that reason. In other words, unless you continue to send high-quality microblogs to prove that you rely on ability rather than luck, fans will increase by forwarding.

How many people are there? The following figure is the relationship between the number of forwarded numbers and the number of fans mentioned in the previous study. It's almost a linear relationship! A person with 5000 fans and a person with 1000 fans, micro-boping are almost five times times the number of forwarding. This means that on average, the number of people who have a lot of fans is no higher than those with fewer fans, and they get more forwarding just because they have more fans! The statistic also shows that the average number of tweets per 1000 followers is 1.5 times per tweet, and if your score is better than this one, then you are a higher level.

Some people think that many micro-blogging can raise fans, some people think that micro-blogging is not expensive, and this study tells us that your forwarding probability and the number of your hair does not matter. The following diagram is the relationship between the probability of being forwarded and the number of micro-numbers:

As the picture shows, whether you've sent 500 or 5,000, your next tweet will be forwarded on average almost once. and hair micro-frequency of people accumulate more than the number of bars, which shows that the low frequency does not affect the probability of being forwarded, so it does not affect through the forwarding of the fans.

Conclusion

In a word, contrary to the system, celebrities rely on events, ordinary people do not have events can only rely on recommendations, no one recommended by forwarding, and forwarding by content. The effectiveness of the above means of gaining a fan is a straight line down, far behind the front. And the most useless is the number of your hair. These properties show that we focus on a particular person, in most cases because of the attention to the individual, and not just to see what he is sending.

This article only discusses individual integrated microblogs, all of which are not necessarily applicable to a variety of professional microblogging, such as the micro-blog dedicated to the collection of jokes. It may be easier to get a fan if you just send an account on one side of the content, because someone else has a fixed expectation of your content. This account, though important to the reader, may not be much fun for the writer, equivalent to the NPC (not the Player control role) in the microblog world.

In a word, you want to raise your fans. That being the case, just ignore the number of fans. Maybe the real fun of blogging is not to attract fans, but to make a good speech!

The authors note: both of the studies used in this article are for Twitter, and I am not sure whether these studies are consistent with China's national conditions. One interesting phenomenon is that Sina Weibo seems to have a much larger order of magnitude than Twitter. It's good to have 5000 fans on Twitter, and 10,000 of Sina Weibo is not necessarily a decent number. "Do not use" common sense "understanding of the complex world," the study introduced in two months 74 million of the tweets in dozens of were forwarded more than thousands of times, and the number of forwarding reached more than one or two--in Sina Weibo, forwarding million times is not conspicuous. So once again called on insight to take domestic micro-bo more do research. In addition, my microblog account is @GK colleagues in the wild, welcome attention!