【Data Analysis】The long tail effect of 𝓜𝓪𝓽𝓽𝓮𝓻𝓼

The long tail effect believes that in the Internet age, as storage costs are approaching zero, many products with low sales volume can remain in online stores to provide consumers with choices. As long as there are enough products with low sales volume, the combined sales volume is also considerable. .

When used in Matters, it can be considered that after the article is published, after a few days before you can get a lot of claps, you can continue to get a small amount of claps. As long as you have enough articles, the accumulated number of claps is also very objective. To put it more vernacularly, the better the long tail effect, the higher your passive income. Of course, since the LIKE coins obtained by writing in Matters are not too many, this passive income is limited no matter how good it is. The above concepts are my personal understanding. If there are any mistakes, please leave a message below.

▶️ Does posting on Matters have a long tail?

I have the impression that I occasionally see people mentioning Matters' old articles that basically no one reads, because Matters' recommendation mechanism is not good. In this case, will there still be the so-called long tail effect of posting in Matters? So I downloaded half a year of data to study the performance of the long tail effect of the entire Matters, the following charts are based on all Matters published articles from August 2021 to February 2022 and the time they were clapped.

Because only half a year's data is used, only 90 days (three months) of article publication days are taken to calculate the cumulative percentage. The graph shows that the cumulative percentage on the third day is 93.1%, which means that about 7% of the clapping can be obtained for the next 87 days.

Because my own impression is that 3 days after the article is published, there is basically no clapping, so I think the result is better than I thought, I don't know what you think?

▶️ Want to know your own data?

After reading Matters site-wide data, are you curious about the long tail effect of your articles published in Matters?

There are too many articles in Matters. Uncle can't finish them all. He can only get the data for half a year for everyone to see (from September last year to the end of February this year). ).

The percentage in the chart is the same as the one above, and the calculation is only taken for 90 days, so you can expect to get clapping in the future, but you don’t know how many.

The picture placed with JSFiddle is a bit small, if you are not used to it, you can click here to open a new window to view it.

▶️ Afterword

This topic originated from a few weeks ago on Liker Social, I saw someone mentioned that there is still a long tail effect after the Matters article is published. The first reaction was, is there really? There are too few to plug the gap between the teeth, right?

Arranging this data is to confirm my opinion: there is, but it is really very little!

Of course, the post on Matters is not all for that point of LIKE, but I personally feel that those other reasons have nothing to do with the long tail effect.